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Part III - Activities in Cyber Behavior
Published online by Cambridge University Press: 06 December 2024
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- The Cambridge Handbook of Cyber Behavior , pp. 479 - 872Publisher: Cambridge University PressPrint publication year: 2023
References
References
Anderson, C. A., & Bushman, B. J. (2001). Effects of violent video games on aggressive behavior, aggressive cognition, aggressive affect, physiological arousal, and prosocial behavior: A meta-analytic review of the scientific literature. Psychological Science, 12(5), 353–359.CrossRefGoogle ScholarPubMed
Andersson, G., & Cuijpers, P. (2009). Internet-based and other computerized psychological treatments for adult depression: A meta-analysis. Cognitive Behaviour Therapy, 38(4), 196–205.CrossRefGoogle ScholarPubMed
Andrews, G., Cuijpers, P., Craske, M. G., McEvoy, P., & Titov, N. (2010). Computer therapy for the anxiety and depressive disorders is effective, acceptable and practical health care: A meta-analysis. PLoS ONE, 5(10), e13196.CrossRefGoogle ScholarPubMed
Bernard, R. M., Abrami, P. C., Lou, Y., Borokhovski, E., Wade, A., Wozney, L., … & Huang, B. (2004). How does distance education compare with classroom instruction? A meta-analysis of the empirical literature. Review of Educational Research, 74(3), 379–439.CrossRefGoogle Scholar
Bond, R. M., Fariss, C. J., Jones, J. J., Kramer, A. D., Marlow, C., Settle, J. E., & Fowler, J. H. (2012). A 61-million-person experiment in social influence and political mobilization. Nature, 489(7415), 295–298.CrossRefGoogle ScholarPubMed
Blumenthal, D., & Tavenner, M. (2010). The “meaningful use” regulation for electronic health records. New England Journal of Medicine, 363(6), 501–504.CrossRefGoogle Scholar
Buhalis, D., & Law, R. (2008). Progress in information technology and tourism management: 20 years on and 10 years after the Internet – The state of eTourism research. Tourism Management, 29(4), 609–623.CrossRefGoogle Scholar
Buhrmester, M., Kwang, T., & Gosling, S. D. (2016). Amazon’s Mechanical Turk: A new source of inexpensive, yet high-quality data? Perspectives on Psychological Science, 6(1), 3–5.CrossRefGoogle Scholar
Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S., … & PROMIS Cooperative Group. (2010). The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. Journal of Clinical Epidemiology, 63(11), 1179–1194.CrossRefGoogle ScholarPubMed
Charlton, J. P., & Danforth, I. D. (2007). Distinguishing addiction and high engagement in the context of online game playing. Computers in Human Behavior, 23(3), 1531–1548.CrossRefGoogle Scholar
Chaudhry, B., Wang, J., Wu, S., Maglione, M., Mojica, W., Roth, E., … & Shekelle, P. G. (2006). Systematic review: Impact of health information technology on quality, efficiency, and costs of medical care. Annals of Internal Medicine, 144(10), 742–752.CrossRefGoogle ScholarPubMed
Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of Marketing Research, 43(3), 345–354.CrossRefGoogle Scholar
Cook, C., Heath, F., & Thompson, R. L. (2000). A meta-analysis of response rates in web-or internet-based surveys. Educational and Psychological Measurement, 60(6), 821–836.CrossRefGoogle Scholar
Cook, D. A., Hatala, R., Brydges, R., Zendejas, B., Szostek, J. H., Wang, A. T., … & Hamstra, S. J. (2011). Technology-enhanced simulation for health professions education: A systematic review and meta-analysis. Jama, 306(9), 978–988.CrossRefGoogle ScholarPubMed
Couper, M. P. (2000). Web surveys: A review of issues and approaches. The Public Opinion Quarterly, 64(4), 464–494.CrossRefGoogle ScholarPubMed
Crump, M. J., McDonnell, J. V., & Gureckis, T. M. (2013). Evaluating Amazon’s Mechanical Turk as a tool for experimental behavioral research. PLoS ONE, 8(3), e57410.CrossRefGoogle Scholar
Dellarocas, C. (2003). The digitization of word of mouth: Promise and challenges of online feedback mechanisms. Management Science, 49(10), 1407–1424.CrossRefGoogle Scholar
Eysenbach, G., & Köhler, C. (2002). How do consumers search for and appraise health information on the world wide web? Qualitative study using focus groups, usability tests, and in-depth interviews. British Medical Journal, 324(7337), 573–577.CrossRefGoogle ScholarPubMed
Free, C., Phillips, G., Watson, L., Galli, L., Felix, L., Edwards, P., … & Haines, A. (2013). The effectiveness of mobile-health technologies to improve health care service delivery processes: A systematic review and meta-analysis. PLoS Med, 10(1), e1001363.CrossRefGoogle ScholarPubMed
Gentile, D. (2009). Pathological video-game use among youth ages 8 to 18: A national study. Psychological Science, 20(5), 594–602.CrossRefGoogle ScholarPubMed
Godes, D., & Mayzlin, D. (2004). Using online conversations to study word-of-mouth communication. Marketing Science, 23(4), 545–560.CrossRefGoogle Scholar
Granic, I., Lobel, A., & Engels, R. C. (2014). The benefits of playing video games. American Psychologist, 69(1), 66–78.CrossRefGoogle ScholarPubMed
Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? Journal of Interactive Marketing, 18(1), 38–52.CrossRefGoogle Scholar
Hesse, B. W., Nelson, D. E., Kreps, G. L., Croyle, R. T., Arora, N. K., Rimer, B. K., & Viswanath, K. (2005). Trust and sources of health information: The impact of the Internet and its implications for health care providers: findings from the first Health Information National Trends Survey. Archives of Internal Medicine, 165(22), 2618–2624.CrossRefGoogle ScholarPubMed
Hew, K. F., & Brush, T. (2007). Integrating technology into K-12 teaching and learning: Current knowledge gaps and recommendations for future research. Educational Technology Research and Development, 55(3), 223–252.CrossRefGoogle Scholar
Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60(3), 50–68.CrossRefGoogle Scholar
Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853–868.CrossRefGoogle Scholar
Jha, A. K., DesRoches, C. M., Campbell, E. G., Donelan, K., Rao, S. R., Ferris, T. G., … & Blumenthal, D. (2009). Use of electronic health records in US hospitals. New England Journal of Medicine, 360(16), 1628–1638.CrossRefGoogle Scholar
Jøsang, A., Ismail, R., & Boyd, C. (2007). A survey of trust and reputation systems for online service provision. Decision Support Systems, 43(2), 618–644.CrossRefGoogle Scholar
Kirschner, P. A., & Karpinski, A. C. (2010). Facebook® and academic performance. Computers in Human Behavior, 26(6), 1237–1245.CrossRefGoogle Scholar
Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–223.CrossRefGoogle Scholar
Lazer, D., Kennedy, R., King, G., & Vespignani, A. (2014). The parable of Google Flu: traps in big data analysis. Science, 343(6176), 1203–1205.CrossRefGoogle ScholarPubMed
Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism Management, 29(3), 458–468.CrossRefGoogle Scholar
Mason, W., & Suri, S. (2012). Conducting behavioral research on Amazon’s Mechanical Turk. Behavior Research Methods, 44(1), 1–23.CrossRefGoogle ScholarPubMed
Meho, L. I., & Yang, K. (2007). Impact of data sources on citation counts and rankings of LIS faculty: Web of Science versus Scopus and Google Scholar. Journal of the American Society for Information Science and Technology, 58(13), 2105–2125.CrossRefGoogle Scholar
Paolacci, G., Chandler, J., & Ipeirotis, P. G. (2010). Running experiments on Amazon Mechanical Turk. Judgment and Decision Making, 5(5), 411–419.CrossRefGoogle Scholar
Ruiz, J. G., Mintzer, M. J., & Leipzig, R. M. (2006). The impact of e-learning in medical education. Academic Medicine, 81(3), 207–212.CrossRefGoogle ScholarPubMed
Ryan, R. M., Rigby, C. S., & Przybylski, A. (2006). The motivational pull of video games: A self-determination theory approach. Motivation and Emotion, 30(4), 344–360.CrossRefGoogle Scholar
Webb, T., Joseph, J., Yardley, L., & Michie, S. (2010). Using the Internet to promote health behavior change: A systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. Journal of Medical Internet Research, 12(1), e4.CrossRefGoogle Scholar
Wilson, R. E., Gosling, S. D., & Graham, L. T. (2012). A review of Facebook research in the social sciences. Perspectives on Psychological Science, 7(3), 203–220.CrossRefGoogle ScholarPubMed
Xiang, Z., & Gretzel, U. (2010). Role of social media in online travel information search. Tourism Management, 31(2), 179–188.CrossRefGoogle Scholar
Yee, N. (2006). Motivations for play in online games. CyberPsychology & Behavior, 9(6), 772–775.CrossRefGoogle ScholarPubMed
References
Ahola Kohut, S., LeBlanc, C., O’Leary, K., McPherson, A. C., McCarthy, E., Nguyen, C., & Stinson, J. (2018). The Internet as a source of support for youth with chronic conditions: A qualitative study. Child: Care, Health & Development, 44(2), 212–220.CrossRefGoogle ScholarPubMed
Anderson, A. (2018). Online health information and public knowledge, attitudes, and behaviours regarding antibiotics in the UK: Multiple regression analysis of Wellcome Monitor and Eurobarometer Data [Research Support, Non-U.S. Gov’t]. PLoS ONE, 13(10), e0204878. https://doi.org/https://dx.doi.org/10.1371/journal.pone.0204878CrossRefGoogle ScholarPubMed
Anderson, M., & Jiang, J. (2018). Teens, social media & technology 2018. Pew Research Center, 31, 2018.Google Scholar
Arbuckle, C., Tomaszewski, D., Brown, L., Schommer, J., Morisky, D., Parlett-Pelleriti, C., & Linstead, E. (2019). Exploring the relationship of digital information sources and medication adherence. Computers in Biology & Medicine, 109, 303–310. https://doi.org/https://dx.doi.org/10.1016/j.compbiomed.2019.04.023CrossRefGoogle ScholarPubMed
Beck, F., Richard, J. B., Nguyen-Thanh, V., Montagni, I., Parizot, I., & Renahy, E. (2014). Use of the internet as a health information resource among French young adults: Results from a nationally representative survey. Journal of Medical Internet Research, 16(5), e128. https://doi.org/https://dx.doi.org/10.2196/jmir.2934CrossRefGoogle ScholarPubMed
Benitez-Andrades, J. A., Arias, N., Garcia-Ordas, M. T., Martinez-Martinez, M., & Garcia-Rodriguez, I. (2020). Feasibility of social-network-based eHealth intervention on the improvement of healthy habits among children. Sensors, 20(5), 04. https://doi.org/https://dx.doi.org/10.3390/s20051404CrossRefGoogle ScholarPubMed
Bennett, S. J., Maton, K. A., & Lervin, L. K. (2008). The “digital natives” debate: A critical review of the evidence. British Journal of Educational Technology, 39(5), 775–786. https://doi.org/doi:10.1111/j.1467–8535.2007.00793.xCrossRefGoogle Scholar
Best, P., Manktelow, R., & Taylor, B. J. (2016). Social work and social media: Online help-seeking and the mental well-being of adolescent males. British Journal of Social Work, 46(1), 257–276.CrossRefGoogle Scholar
Booth, K. M., & Trauth, E. M. (2019). Moving beyond text: How teens evaluate video-based high stakes health information via social media. In: Taylor, N., Christian-Lamb, C., Martin, M., & Nardi, B. (eds), Information in contemporary society. iConference 2019. Lecture Notes in Computer Science, vol. 11420. Springer, Cham.Google Scholar
Caiata-Zufferey, M., & Schulz, P. J. (2012). Physicians’ communicative strategies in interacting with internet-informed patients: Results from a qualitative study. Health Communication, 27(8), 738–749. https://doi.org/10.1080/10410236.2011.636478CrossRefGoogle ScholarPubMed
Casey, A., Goodyear, V. A., & Armour, K. M. (2017). Rethinking the relationship between pedagogy, technology and learning in health and physical education. Sport, Education and Society, 22(2), 288–304.CrossRefGoogle Scholar
Cohn, A., & Richters, J. (2013). “My vagina makes funny noises”: Analyzing online forums to assess the real sexual health concerns of young people. International Journal of Sexual Health, 25(2), 93–103.CrossRefGoogle Scholar
Coiro, J., Coscarelli, C., Maykel, C., & Forzani, E. (2015). Investigating criteria that seventh graders use to evaluate the quality of online information. Journal of Adolescent & Adult Literacy, 59(3), 287–297.CrossRefGoogle Scholar
Crawford, G. B. (2007). Brain-based teaching with adolescent learning in mind. Corwin Press.Google Scholar
Davis, W. M., Shoveller, J. A., Oliffe, J. L., & Gilbert, M. (2012). Young people’s perspectives on the use of reverse discourse in web-based sexual-health interventions. Culture, Health & Sexuality, 14(9), 1065–1079. https://doi.org/http://dx.doi.org/10.1080/13691058.2012.714800CrossRefGoogle ScholarPubMed
De Jans, S., Van de Sompel, D., De Veirman, M., & Hudders, L. (2020). #Sponsored! How the recognition of sponsoring on Instagram posts affects adolescents’ brand evaluations through source evaluations. Computers in Human Behavior, 106342.CrossRefGoogle Scholar
Delmonaco, D., Marcu, G., & Haimson, O. L. (2020). Search engines and the sex education information practices of LGBTQ+ youth. Proceedings of the Association for Information Science and Technology, 57(1), e364.CrossRefGoogle Scholar
Diviani, N. (2019). On the centrality of information appraisal in health literacy research. HLRP: Health Literacy Research and Practice, 3(1), e21–e24.CrossRefGoogle ScholarPubMed
Fleary, S. A., Joseph, P., & Pappagianopoulos, J. E. (2018). Adolescent health literacy and health behaviors: A systematic review. Journal of Adolescence, 62, 116–127. https://doi.org/https://dx.doi.org/10.1016/j.adolescence.2017.11.010CrossRefGoogle ScholarPubMed
Freedman, L. B. (2003). The educational potential of the Internet: An analysis of adolescents’ abilities to search the Internet, gather, evaluate and retain health-related information. Dissertation Abstracts International Section A: Humanities and Social Sciences, 63(9-A), 3106.Google Scholar
Freeman, J. L., Caldwell, P. H. Y., Bennett, P. A., & Scott, K. M. (2018). How adolescents search for and appraise online health information: A systematic review. The Journal of Pediatrics, 195, 244–255. e241. https://doi.org/https://doi.org/10.1016/j.jpeds.2017.11.031CrossRefGoogle ScholarPubMed
Freeman, J. L., Caldwell, P. H. Y., & Scott, K. M. (2020). The role of trust when adolescents search for and appraise online health information. The Journal of Pediatrics, 221, 215–223. e215.CrossRefGoogle ScholarPubMed
Gard, M. (2014). eHPE: A history of the future. Sport, Education and Society, 19(6), 827–845.CrossRefGoogle Scholar
Gazibara, T., Cakic, J., Cakic, M., Grgurevic, A., & Pekmezovic, T. (2020). Searching for online health information instead of seeing a physician: A cross-sectional study among high school students in Belgrade, Serbia. International Journal of Public Health, 02, 02. https://doi.org/https://dx.doi.org/10.1007/s00038-020–01471–7Google Scholar
Goodyear, V., Armour, K., & Wood, H. (2018). The impact of social media on young people’s health and wellbeing: Evidence, guidelines and actions. Birmingham, UK. University of Birmingham.Google Scholar
Goodyear, V., & Quennerstedt, M. (2020). #Gymlad – Young boys learning processes and health-related social media. Qualitative Research in Sport, Exercise and Health, 12(1), 18–33.CrossRefGoogle ScholarPubMed
Goodyear, V. A., Armour, K. M., & Wood, H. (2019). Young people and their engagement with health-related social media: New perspectives. Sport, Education and Society, 24(7), 673.CrossRefGoogle ScholarPubMed
Gray, N. J., & Klein, J. D. (2006). Adolescents and the Internet: Health and sexuality information. Current Opinion in Obstetrics and Gynecology, 18(5), 519–524.CrossRefGoogle ScholarPubMed
Gray, N. J., Klein, J. D., Cantrill, J. A., & Noyce, P. R. (2002). Adolescent girls’ use of the Internet for health information: Issues beyond access. Journal of Medical Systems, 26(6), 545–553.CrossRefGoogle ScholarPubMed
Gray, N. J., Klein, J. D., Noyce, P. R., Sesselberg, T. S., & Cantrill, J. A. (2005a). Health information-seeking behaviour in adolescence: The place of the Internet. Social Science & Medicine, 60(7), 1467–1478.CrossRefGoogle ScholarPubMed
Gray, N. J., Klein, J. D., Noyce, P. R., Sesselberg, T. S., & Cantrill, J. A. (2005b). The Internet: A window on adolescent health literacy. Journal of Adolescent Health, 37(3), 243. e241–243, e247.CrossRefGoogle ScholarPubMed
Guilamo-Ramos, V., Lee, J. J., Kantor, L. M., Levine, D. S., Baum, S., & Johnsen, J. (2015). Potential for using online and mobile education with parents and adolescents to impact sexual and reproductive health. Prevention Science, 16(1), 53–60.CrossRefGoogle ScholarPubMed
Hansen, D. L., Derry, H. A., Resnick, P. J., & Richardson, C. R. (2003). Adolescents searching for health information on the Internet: An observational study. Journal of Medical Internet Research, 5(4), e25.CrossRefGoogle ScholarPubMed
Hausmann, J. S., Touloumtzis, C., White, M. T., Colbert, J. A., & Gooding, H. C. (2017). Adolescent and young adult use of social media for health and its implications. Journal of Adolescent Health, 60(6), 714–719.CrossRefGoogle Scholar
Henderson, E. M., Keogh, E., & Eccleston, C. (2014). Why go online when you have pain? A qualitative analysis of teenagers’ use of the Internet for pain management advice. Child: Care, Health & Development, 40(4), 572–579. https://doi.org/http://dx.doi.org/10.1111/cch.12072CrossRefGoogle Scholar
Hove, T., Paek, H.-J., & Isaacson, T. (2011). Using adolescent eHealth literacy to weigh trust in commercial web sites: The more children know, the tougher they are to persuade. Journal of Advertising Research, 51(3), 524–537.CrossRefGoogle Scholar
Jain, A. V., & Bickham, D. (2014). Adolescent health literacy and the Internet: Challenges and opportunities. Current Opinion in Pediatrics, 26(4), 435–439. https://journals.lww.com/co-pediatrics/fulltext/2014/08000/Adolescent_health_literacy_and_the_Internet__.7.aspxCrossRefGoogle ScholarPubMed
Jiménez-Pernett, J., de Labry-Lima, A. O., Bermúdez-Tamayo, C., García-Gutiérrez, J. F., & del Carmen Salcedo-Sánchez, M. (2010). Use of the internet as a source of health information by Spanish adolescents. BMC Medical Informatics and Decision Making, 10(1), 6.CrossRefGoogle ScholarPubMed
Jiménez-Pernett, J., Olry de Labry-Lima, A., García-Gutiérrez, J. F., Salcedo-Sánchez, M. d. C., & Bermudez-Tamayo, C. (2010). Sex differences in the use of the Internet as a source of health information among adolescents. Telemedicine and e-Health, 16(2), 145–153.CrossRefGoogle ScholarPubMed
Jones, R. K., & Biddlecom, A. E. (2011). The more things change…: the relative importance of the internet as a source of contraceptive information for teens. Sexuality Research and Social Policy, 8(1), 27–37.CrossRefGoogle Scholar
Jones, R. K., & Biddlecom, A. E. (2011). Is the Internet filling the sexual health information gap for teens? An exploratory study. Journal of Health Communication, 16(2), 112–123.CrossRefGoogle Scholar
Jørgensen, K. M. (2016). The media go-along: Researching mobilities with media at hand. MedieKultur: Journal of Media and Communication Research, 32(60), 32–49.CrossRefGoogle Scholar
Kamel Boulos, M. N., & Wheeler, S. (2007). The emerging Web 2.0 social software: An enabling suite of sociable technologies in health and health care education 1. Health Information & Libraries Journal, 24(1), 2–23.CrossRefGoogle Scholar
Kang, M., Robards, F., Sanci, L., Steinbeck, K., Jan, S., Hawke, C., Luscombe, G., Kong, M., & Usherwood, T. (2018). Access 3: Young people and the health system in the digital age-final research report. Department of General Practice Westmead, the University of Sydney and the Australian Centre for Public and Population Health Research, the University of Technology Sydney, Australia.Google Scholar
Kortum, P., Edwards, C., & Richards-Kortum, R. (2008). The impact of inaccurate Internet health information in a secondary school learning environment. Journal of Medical Internet Research, 10(2), e17. https://doi.org/http://dx.doi.org/10.2196/jmir.986CrossRefGoogle Scholar
Lariscy, R., Reber, B., & Paek, H.-J. (2011). Exploration of health concerns and the role of social media information among rural and urban adolescents: A preliminary study. International Electronic Journal of Health Education, 14, 16–36.Google Scholar
Lea, S., Martins, A., Morgan, S., Cargill, J., Taylor, R. M., & Fern, L. A. (2018). Online information and support needs of young people with cancer: A participatory action research study. Adolescent Health, Medicine and Therapeutics, 9, 121.CrossRefGoogle Scholar
Leary, M. P., Clegg, E. N., Santella, M. E., Murray, P. J., Downs, J. S., & Olfert, M. D. (2019). Consumption of health-related content on social media among adolescent girls: Mixed-methods pilot study. JMIR Formative Research, 3(1), e11404. https://doi.org/https://dx.doi.org/10.2196/11404CrossRefGoogle ScholarPubMed
Lenhart, A. (2015). Teens, social media & technology overview 2015. Pew Research Center.Google Scholar
Li, S., Feng, B., Liao, W., & Pan, W. (2020). Internet use, risk awareness, and demographic characteristics associated with engagement in preventive behaviors and testing: Cross-sectional survey on COVID-19 in the United States. Journal of Medical Internet Research, 22(6), e19782. https://doi.org/https://dx.doi.org/10.2196/19782CrossRefGoogle ScholarPubMed
Litras, A., Latreille, S., & Temple-Smith, M. (2015). Dr Google, porn and friend-of-a-friend: Where are young men really getting their sexual health information?. Sexual Health, 12(6), 488–494.CrossRefGoogle ScholarPubMed
McKinnon, K. A., HY Caldwell, P., & Scott, K. M. (2020). How adolescent patients search for and appraise online health information: A pilot study. Journal of Paediatrics and Child Health, 56(8), 1270–1276.CrossRefGoogle ScholarPubMed
McPherson, A. C., Gofine, M. L., & Stinson, J. (2014). Seeing is believing? A mixed-methods study exploring the quality and perceived trustworthiness of online information about chronic conditions aimed at children and young people. Health Communication, 29(5), 473–482.CrossRefGoogle ScholarPubMed
Mian, A., & Khan, S. (2020). Coronavirus: The spread of misinformation. BMC Medicine, 18(1), 1–2.CrossRefGoogle ScholarPubMed
Mitchell, K. J., Ybarra, M. L., Korchmaros, J. D., & Kosciw, J. G. (2014). Accessing sexual health information online: Use, motivations and consequences for youth with different sexual orientations. Health Education Research, 29(1), 147–157.CrossRefGoogle ScholarPubMed
Morris, M. E. (2018). Left to our own devices: Outsmarting smart technology to reclaim our relationships, health, and focus. MIT Press. https://mitpress.mit.edu/books/left-our-own-devicesCrossRefGoogle Scholar
Muse, K., McManus, F., Leung, C., Meghreblian, B., & Williams, J. M. (2012). Cyberchondriasis: Fact or fiction? A preliminary examination of the relationship between health anxiety and searching for health information on the Internet [Research Support, Non-U.S. Gov’t]. Journal of Anxiety Disorders, 26(1), 189–196. https://doi.org/https://dx.doi.org/10.1016/j.janxdis.2011.11.005CrossRefGoogle ScholarPubMed
Nordheim, L. V., Gundersen, M. W., Espehaug, B., Guttersrud, Ø., & Flottorp, S. (2016). Effects of school-based educational interventions for enhancing adolescents abilities in critical appraisal of health claims: A systematic review. PLoS ONE, 11(8), e0161485.CrossRefGoogle ScholarPubMed
Norman, C. D., & Skinner, H. A. (2006). eHealth literacy: Essential skills for consumer health in a networked world. Journal of Medical Internet Research, 8(2), e9.CrossRefGoogle Scholar
Oeldorf-Hirsch, A., High, A. C., & Christensen, J. L. (2019). Count your calories and share them: Health benefits of sharing mhealth information on social networking sites. Health Communication, 34(10), 1130–1140. https://doi.org/https://dx.doi.org/10.1080/10410236.2018.1465791CrossRefGoogle ScholarPubMed
Ortiz, R., Shafer, A., Cates, J., & Coyne-Beasley, T. (2015). Assessing feasibility and strategies for clinicians to communicate via social media with adolescent patients about HPV vaccination. Journal of Adolescent Health, 56(2), S22. https://doi.org/http://dx.doi.org/10.1016/j.jadohealth.2014.10.045CrossRefGoogle Scholar
Patton, G. C., Sawyer, S. M., Santelli, J. S., Ross, D. A., Afifi, R., Allen, N. B., Arora, M., Azzopardi, P., Baldwin, W., & Bonell, C. (2016). Our future: A Lancet commission on adolescent health and wellbeing. The Lancet, 387(10036), 2423–2478.CrossRefGoogle ScholarPubMed
Radovic, A., McCarty, C. A., Katzman, K., & Richardson, L. P. (2018). Adolescents’ perspectives on using technology for health: Qualitative study. JMIR Pediatrics and Parenting, 1(1), e2.CrossRefGoogle ScholarPubMed
Ralph, L. J., Berglas, N. F., Schwartz, S. L., & Brindis, C. D. (2011). Finding teens in TheirSpace: Using social networking sites to connect youth to sexual health services. Sexuality Research & Social Policy: A Journal of the NSRC, 8(1), 38–49. https://doi.org/http://dx.doi.org/10.1007/s13178-011–0043–4CrossRefGoogle Scholar
Rideout, V. (2001) Generation Rx.com: How young people use the internet for health information. Henry J. Kaiser Family Foundation.Google Scholar
Robards, F., Kang, M., Sanci, L., Steinbeck, K., Jan, S., Hawke, C., Kong, M., & Usherwood, T. (2017). ACCESS 3: Young people’s healthcare journeys, preliminary report. http://sydney.edu.au/medicine/general-practice/research/access.phpGoogle Scholar
Selkie, E. M., Benson, M., & Moreno, M. (2011). Adolescents’ views regarding uses of social networking websites and text messaging for adolescent sexual health education. American Journal of Health Education, 42(4), 205–212.CrossRefGoogle ScholarPubMed
Selwyn, N. (2009). The digital native–myth and reality. Aslib Proceedings, 61(4), 364–379.CrossRefGoogle Scholar
Simon, L. (2013). Adolescents’ sex education using new digital media: The personal motivations and interactive experiences of young people online at Reddit.com [Conference abstract]. European Journal of Contraception and Reproductive Health Care, 18, S224–S225. https://doi.org/http://dx.doi.org/10.3109/13625187.2013.793038Google Scholar
Siow, T. R., Soh, I. P., Sreedharan, S., Das De, S., Tan, P. P., Seow, A., & Lun, K. C. (2003). The Internet as a source of health information among Singaporeans: Prevalence, patterns of health surfing and impact on health behaviour. Annals of the Academy of Medicine, Singapore, 32(6), 807–813.CrossRefGoogle ScholarPubMed
Skinner, H., Biscope, S., Poland, B., & Goldberg, E. (2003). How adolescents use technology for health information: Implications for health professionals from focus group studies. Journal of Medical Internet Research, 5(4), e32.CrossRefGoogle ScholarPubMed
Smith, L. W., Liu, B., Degenhardt, L., Richters, J., Patton, G., Wand, H., Cross, D., Hocking, J. S., Skinner, S. R., & Cooper, S. (2016). Is sexual content in new media linked to sexual risk behaviour in young people? A systematic review and meta-analysis. Sexual Health, 13(6), 501–515.CrossRefGoogle Scholar
Stars, I., & Rubene, Z. (2020). A phenomenographic study of adolescents’ conceptions of health information appraisal as a critical component of adolescent health literacy. Acta Paedagogica Vilnensia, 44, 62–80.CrossRefGoogle Scholar
Stellefson, M., Hanik, B., Chaney, J. D., & Tennant, B. (2012). Analysis of ehealth search perspectives among female college students in the health professions using Q methodology. Journal of Medical Internet Research, 14(2), e60.CrossRefGoogle ScholarPubMed
Swist, T., Collin, P., McCormack, J., & Third, A. (2015). Social media and the wellbeing of children and young people: A literature review. Western Sydney University Open Access Collection. Retrieved from www.uws.edu.au/__data/assets/pdf_file/0019/930502/Social_media_and_children_and_young_people.pdfGoogle Scholar
Syed-Abdul, S., Fernandez-Luque, L., Jian, W.-S., Li, Y.-C., Crain, S., Hsu, M.-H., Wang, Y.-C., Khandregzen, D., Chuluunbaatar, E., & Nguyen, P. A. (2013). Misleading health-related information promoted through video-based social media: Anorexia on YouTube. Journal of Medical Internet Research, 15(2), e30.CrossRefGoogle ScholarPubMed
TheLancet. (2018). Children and social media. The Lancet, 391(10116), 95. https://doi.org/10.1016/S0140-6736(18)30049–7CrossRefGoogle Scholar
Van Der Velden, M., & El Emam, K. (2013). “Not all my friends need to know”: A qualitative study of teenage patients, privacy, and social media. Journal of the American Medical Informatics Association, 20(1), 16–24.CrossRefGoogle ScholarPubMed
Wartella, E., Rideout, V., Montague, H., Beaudoin-Ryan, L., & Lauricella, A. (2016). Teens, health and technology: A national survey. Media and Communication, 4(3), 13–23.CrossRefGoogle Scholar
Wartella, E., Rideout, V., Zupancic, H., Beaudoin-Ryan, L., & Lauricella, A. (2015). Teens, health, and technology: A national survey. Northwestern University. https://cmhd.northwestern.edu/wp-content/uploads/2015/05/1886_1_SOC_ConfReport_TeensHealthTech_051115.pdfGoogle Scholar
White, R. W., & Horvitz, E. (2009). Cyberchondria: Studies of the escalation of medical concerns in web search. ACM Transactions on Information Systems (TOIS), 27(4), 23.CrossRefGoogle Scholar
Whitlock, J. L., Powers, J. L., & Eckenrode, J. (2006). The virtual cutting edge: The internet and adolescent self-injury. Developmental Psychology, 42(3), 407.CrossRefGoogle ScholarPubMed
Williamson, B. (2015). Algorithmic skin: Health-tracking technologies, personal analytics and the biopedagogies of digitized health and physical education. Sport, Education and Society, 20(1), 133–151.CrossRefGoogle Scholar
Yardi, S., Caldwell, P. H., Barnes, E. H., & Scott, K. M. (2018). Determining parents’ patterns of behaviour when searching for online information on their child’s health. Journal of Paediatrics and Child Health, 54(11), 1246–1254.CrossRefGoogle ScholarPubMed
Ybarra, M., & Suman, M. (2006). Reasons, assessments and actions taken: Sex and age differences in uses of Internet health information. Health Education Research, 23(3), 512–521. https://doi.org/10.1093/her/cyl062CrossRefGoogle ScholarPubMed
Yfoundations. (2015). Youth Health and Wellness. Youth Refuge Action Group. Retrieved 17 February 2017 from http://yfoundations.org.au/wp-content/uploads/2015/04/Youth-Health-and-Wellness_April2015_FINAL2.pdfGoogle Scholar
References
Aebli, A. (2009). Tourists’ motives for gamified technology use. Annals of Tourism Research, 78, 102753, https://doi.org/10.1016/j.annals.2019.102753CrossRefGoogle Scholar
Buhalis, D. (2019), Technology in tourism-from information communication technologies to eTourism and smart tourism towards ambient intelligence tourism: A perspective article. Tourism Review, 75(1), 267–272. https://doi.org/10.1108/TR-06-2019-0258CrossRefGoogle Scholar
Buhalis, D. & Foerste, M. (2015). SoCoMo marketing for travel and tourism: Empowering co-creation of value. Journal of Destination Marketing and Management, 4, 151–161.CrossRefGoogle Scholar
Buhalis, D. & Law, R. (2008). Progress in information technology and tourism management: 20 years on and 10 years after the Internet – The state of e-tourism research. Tourism Management, 29(4), 609–623.CrossRefGoogle Scholar
Buhalis, D., Leung, D., Law, R. (2011). eTourism: Critical information and communication technologies for tourism destinations. In: Wang, Y., Pizam, A. (Eds.), Destination marketing and management: Theories and applications. CABI, New York, pp. 205–224.CrossRefGoogle Scholar
Buhalis, D. & Sinarta, Y. (2019). Real-time co-creation and nowness service: Lessons from tourism and hospitality. Journal of Travel & Tourism Marketing, 36, 563–582.CrossRefGoogle Scholar
Buonincontri, P. & Micera, R. (2016). The experience co-creation in smart tourism destinations: A multiple case analysis of European destinations. Information Technology and Tourism, 16, 285–315.CrossRefGoogle Scholar
Campos, A. C., Mendes, J., Oom do Valle, P. & Scott, N. (2018). Co-creation of tourist experiences: A literature review. Current Issues in Tourism, 21(4), 369–400 DOI: http://dx.doi.org/10.1080/13683500.2015.1081158CrossRefGoogle Scholar
Choe, Y. & Fesenmaier, D. R. (2017). The quantified traveller: Implications for smart tourism development. In Analytics in Smart Tourism Design, Tourism on the Verge. Xiang, Z., Fesenmaier, D. R., Eds. Springer International Publishing, pp. 65–77.CrossRefGoogle Scholar
Dayour, F., Park, S. & Kimb, A. N. (2019) Backpackers’ perceived risks towards smartphone usage and risk reduction strategies: A mixed methods study. Tourism Management. 72, 52–68. https://doi.org/10.1016/j.tourman.2018.11.003CrossRefGoogle Scholar
Femenia-Serra, F. & Neuhofer, B. (2018). Smart tourism experiences: Conceptualization, key dimensions and research agenda. Journal of Regional Research, 42, 129–150.Google Scholar
Femenia-Serra, F., Neuhofer, B. & Ivars-Baidal, J. A. (2019). Towards a conceptualization of smart tourists and their role within the smart destination scenario. The Service Industries Journal, 39, 109–133.CrossRefGoogle Scholar
Flavián, C., Ibáñez-Sánchez, S. & Orús, C. (2019). The impact of virtual, augmented and mixed reality technologies on the customer experience. Journal of Business Research, 100, 547–560. https://doi.org/10.1016/j.jbusres.2018.10.050CrossRefGoogle Scholar
Gretzel, U., Reino, S., Kopera, S. & Koo, C. (2015). Smart tourism challenges. Journal of Tourism, 6, 41–47.Google Scholar
Gretzel, U. Sigala, M., Xiang, Z. & Koo, C. (2015) Smart tourism: Foundations and developments. Electronic Markets, 25, 179–188.CrossRefGoogle Scholar
Gretzel, U., Zhong, L. & Koo, C. (2016). Application of smart tourism to cities. International Journal of Tourist Cities, 2. doi:10.1108/IJTC-04-2016-0007Google Scholar
Hsu, A., King, B., Wang, D. & Buhalis, D. (2016). In-destination tour products and the disrupted tourism industry: Progress and prospects. Information Technology & Tourism, 17, 1–21. https://doi.org/10.1007/s40558-016-0067-yGoogle Scholar
Ingram, C. Caruana, R. & McCabe, S. (2017). PARTicipative inquiry for tourist experience. Annals of Tourism Research, 65, 13–24.CrossRefGoogle Scholar
Khan, S. M., Woo, M., Nam, K. & Chathoth, K. P. (2017). Smart city and smart tourism: A case of Dubai. Sustainability, http://doi.org/10.3390/su9122279CrossRefGoogle Scholar
Kim, J., & Fesenmaier, D. R. (2017). Sharing tourism experiences: The posttrip experience. Journal of Travel Research, 56(1), 28–40. doi:10.1177/0047287515620491CrossRefGoogle Scholar
Kim, M. J. & Hall, C. M. (2019) A hedonic motivation model in virtual reality tourism: Comparing visitors and non-visitors. International Journal of Information Management, 46, 236–249. https://doi.org/10.1016/j.ijinfomgt.2018.11.016CrossRefGoogle Scholar
Kim, M. J. & Hall, M. C. (2020). What drives visitor economy crowdfunding? The effect of digital storytelling on unified theory of acceptance and use of technology. Tourism Management Perspectives, 34, 100638. https://doi.org/10.1016/j.tmp.2020.100638CrossRefGoogle Scholar
Kotler, P., Bowen, J. T. & Makens, J. C. (2019). Marketing for Hospitality and Tourism (5th ed.). Prentice Hall.Google Scholar
Kyung, L. L., Lee, Y. & Yang, B. B. (2019). Exploring the effect of heuristic factors on the popularity of user-curated ‘Best places to visit’ recommendations in an online travel community. Information Processing & Management, 56(4), 1391–1408. https://doi.org/10.1016/j.ipm.2018.03.009Google Scholar
Lalicic, L. & Dickinger, A. (2019). An assessment of user-driven innovativeness in a mobile computing travel platform. Technological Forecasting and Social Change, 144, 233–241. https://doi.org/10.1016/j.techfore.2017.02.024CrossRefGoogle Scholar
Law, R., Buhalis, D. & Cobanoglu, C. (2014). Progress on information and communication technologies in hospitality and tourism. International Journal of Contemporary Hospitality Management, 26(5), 727–750.CrossRefGoogle Scholar
Law, R., Leung, R. & Buhalis, D. (2009). Information technology applications in hospitality and tourism: A review of publications from 2005 to 2007. Journal of Travel & Tourism Marketing, 26(5–6), 599–623 https://doi.org/10.1080/10548400903163160CrossRefGoogle Scholar
Law, R., Qi, S. & Buhalis, D. (2010). Progress in tourism management: A review of website evaluation in tourism research. Tourism Management, 31, 297–313.CrossRefGoogle Scholar
Leung, R. & Law, R. (2007). Information technology publications in leading tourism journals: A study of 1985–2004. Information Technology and Tourism, 9(2), 133–144.CrossRefGoogle Scholar
Leung, D., Law, R., van Hoof, H. & Buhalis, D. (2013). Social media in tourism and hospitality: A literature review. Journal of Travel & Tourism Marketing, 30(1–2), 3–22.CrossRefGoogle Scholar
Leung, X. Y., Xue, L. & Bai, B. (2015). Internet marketing research in hospitality and tourism: A review and journal preferences. International Journal of Contemporary Hospitality Management, 27(7), 1556–1572.CrossRefGoogle Scholar
Li, C., Guo, S., Wang, C. L. & Zhang, J. (2019). Veni, vidi, vici: The impact of social media on virtual acculturation in tourism context. Technological Forecasting and Social Change, 145, 513–522. https://doi.org/10.1016/j.techfore.2019.01.013CrossRefGoogle Scholar
London School of Economics. (2016). Travel Distribution: The End of the World as We Know It? LSE Consulting & Amadeus.Google Scholar
Lyu, J., Li, M. & Law, R. (2019) Experiencing P2P accommodations: Anecdotes from Chinese customers. International Journal of Hospitality Management, 77, 323–332. https://doi.org/10.1016/j.ijhm.2018.07.012CrossRefGoogle Scholar
Malone, C., McKechnie, S. & Tynan, C. (2017). Tourists’ emotions as a resource for customer value creation, concretion, and destruction: A customer-grounded understanding. Journal of Travel Research, 57(7), 843–855.CrossRefGoogle Scholar
Morrison, A. M. (2019). Marketing and Managing Tourism Destinations (2nd ed.). Routledge.Google Scholar
Munar, A. M. (2016). Social media. In Encyclopedia of Tourism. Jafari, J. & Xiao, H. Eds. Springer, pp. 869–871.CrossRefGoogle Scholar
Navío-Marco, J., Ruiz-Gómeza, L. M. & Sevilla-Sevilla, C. (2018). Progress in information technology and tourism management: 30 years on and 20 years after the internet – Revisiting Buhalis & Law’s landmark study about eTourism. Tourism Management, 69, 460–470.CrossRefGoogle Scholar
Neuhofer, B., Buhalis, D. & Ladkin, A. (2014). A typology of technology enhanced experiences. International Journal of Tourism Research, 16, 340–350.CrossRefGoogle Scholar
Park, O-J., Kim, M. G. & Ryu, J-H. (2019). Interface effects of online media on tourists’ attitude changes. Tourism Management Perspectives, 30, 262–274, https://doi.org/10.1016/j.tmp.2019.03.005CrossRefGoogle Scholar
Pesonen, A. J. (2013). Information and communications technology and market segmentation in tourism: A review. Tourism Review, 68(2), 14–30.CrossRefGoogle Scholar
Shaw, C. & Ivens, J. (2002). Building Great Customer Experiences. Palgrave Macmillan.CrossRefGoogle Scholar
Shen, S., Sotiriadis, M. & Zhou, Q. (2020). Could smart tourists be sustainable and responsible as well? The contribution of Social Networking Sites to improving their sustainable and responsible behaviour. Sustainability, 12(4), 1470; https://doi.org/10.3390/su12041470CrossRefGoogle Scholar
Shen, S., Sotiriadis, M. & Zhang, Y. (2020). The influence of smart technologies on customer journey in tourist attractions within the smart tourism management framework. Sustainability, 12(10), 4157; https://doi.org/10.3390/su12104157CrossRefGoogle Scholar
Shostack, G. L. (1984). Designing services that deliver. Harvard Business Review, 62(1), 133–139.Google Scholar
Sigala, M. (2015). The application and impact of gamification funware on trip planning and experiences: The case of TripAdvisor’s funware. Electronic Markets, 25(3), 189–209.CrossRefGoogle Scholar
Sigala, M., Christou, E. & Gretzel, U. (2012). Social Media in Travel, Tourism and Hospitality: Theory, Practice and Cases. Ashgate.Google Scholar
Sotiriadis, M. (2017). Sharing tourism experiences in social media: A literature review and a set of suggested business strategies. International Journal of Contemporary Hospitality Management, 29(1), 179–225.CrossRefGoogle Scholar
Standing, C., Tang-Taye, J-P. & Boyer, M. (2014). The impact of the Internet in travel and tourism: A research review 2001–2010. Journal of Travel & Tourism Marketing, 31(1), 82–113. https://doi.org/10.1080/10548408.2014.861724CrossRefGoogle Scholar
Thakran, K. & Verma, R. (2013). The emergence of hybrid online distribution channels in travel, tourism and hospitality. Cornell Hospitality Quarterly, 54(3), 240–247.CrossRefGoogle Scholar
Ukpabi, D. C. & Karjaluoto, H. (2017). Consumers’ acceptance of information and communications technology in tourism: A review. Telematics and Informatics, 34(5), 618–644. https://doi.org/10.1016/j.tele.2016.12.002CrossRefGoogle Scholar
Ukpabi, D. C. & Karjaluoto, H. (2018). What drives travelers’ adoption of user-generated content? A literature review. Tourism Management Perspectives. 28, 251–273. https://doi.org/10.1016/j.tmp.2018.03.006CrossRefGoogle Scholar
Voss, C. & Zomerdijk, L. (2007). Innovation in experiential services – An empirical view. In: DTI (Ed.). Innovation in Services. DTI, pp. 97–134. Available at www.dti.gov.uk/files/file39965.pdf. Accessed on 20 May 2020.Google Scholar
Wang, D., Park, S. & Fesenmaier, D. R. (2012). The role of smartphones in mediating the touristic experience. Journal of Travel Research, 51, 371–387.CrossRefGoogle Scholar
Xiang, Z., Mignini, V. P. & Fesenmaier, D. R. (2015). Information technology and consumer behavior in travel and tourism: Insights from travel planning using the internet. Journal of Retail Consumer Services, 22, 244–249.CrossRefGoogle Scholar
Yachin, J. M. (2018). The ‘customer journey’: Learning from customers in tourism experience encounters. Tourism Management Perspectives, 28, 201–210.CrossRefGoogle Scholar
Ye, H. B., Ye, H. & Law, R. (2020). Systematic review of smart tourism research. Sustainability, 12, 3401.CrossRefGoogle Scholar
Yu, C-E. & Sun, R. (2019). The role of Instagram in the UNESCO’s creative city of gastronomy: A case study of Macau. Tourism Management, 75, 257–268. https://doi.org/10.1016/j.tourman.2019.05.011CrossRefGoogle Scholar
Zeng, B. & Gerritsen, R. (2014). What do we know about social media in tourism? A review. Tourism Management Perspectives, 10, 27–36.CrossRefGoogle Scholar
Zhang, L. & Yang, J. (2016). Smart tourism. In Encyclopedia of Tourism. Jafari, J. and Xiao, H. Eds. Springer, pp. 862–863.CrossRefGoogle Scholar
References
Anderson, M.L. and Magruder, J. (2013). Does Yelp affect restaurant demand? ARE Update – University of California Gianni Foundation of Agricultural Economics, 16(5), 1–4.Google Scholar
Berger, J. (2014). Word of mouth and interpersonal communication: A review and directions for future research, Journal of Consumer Psychology, 24(4), 586–607.CrossRefGoogle Scholar
Berger, J., Sorensen, A.T., and Rasmussen, S.J. (2010). Positive effects of negative publicity: When negative reviews increase sales, Marketing Science, 29(5), 815–827.CrossRefGoogle Scholar
Berger, J., Humphreys, A., Ludwig, S., Moe, W., Netzer, O., and Schweidel, D. (2019). Uniting the tribes: Using text for marketing insight, Journal of Marketing, 84(1), 1–25.CrossRefGoogle Scholar
Cao, Q., Duan, W., and Gan, Q. (2011). Exploring determinants of voting for the “helpfulness” of online user reviews: A text mining approach, Decision Support Systems, 50(2), 511–521.CrossRefGoogle Scholar
Chae, I., Stephen, A.T., Bart, Y., and Yao, D. (2017). Spillover effects in seeded word-of-mouth marketing campaigns, Marketing Science, 36(1), 89–104.CrossRefGoogle Scholar
Chen, Y., Liu, Y., and Zhang, J. (2012). When do third-party product reviews affect firm value and what can firms do? The case of media critics and professional movie reviews, Journal of Marketing, 76(2), 116–134.CrossRefGoogle Scholar
Chen, Y. and Xie, J. (2008). Online consumer review: Word-of-mouth as a new element of marketing communication mix, Management Science, 54(3), 471–491.CrossRefGoogle Scholar
Chevalier, J.A., Dover, Y., and Mayzlin, D. (2018). Channels of impact: User reviews when quality is dynamic and managers respond, Marketing Science, 37(5), 688–709.CrossRefGoogle Scholar
Chevalier, J. and Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews, Journal of Marketing Research, 43(3), 345–354.CrossRefGoogle Scholar
Chintagunta, P. K., Gopinath, S., and Venkataraman, S. (2010). The effects of online user reviews on movie box office performance: Accounting for sequential rollout and aggregation across local markets, Marketing Science, 29(5), 944–957.CrossRefGoogle Scholar
Cui, G., Lui, H., and Guo, X. (2012). The effect of online consumer reviews on new product sales, International Journal of Electronic Commerce, 17(1), 39–58.CrossRefGoogle Scholar
Dai, H., Chan, C., Mogliner, C. (2020). People rely less on consumer reviews for experiential than material purchases, Journal of Consumer Research, 46(6), 1052–1075.CrossRefGoogle Scholar
Dellarocas, C., Zhang, X., and Awad, N.F. (2007) Exploring the value of online product reviews in forecasting sales: The case of motion pictures, Journal of Interactive Marketing, 21(4), 23–45.CrossRefGoogle Scholar
Duan, W., Gu, B., and Whinston, A.B. (2008). Do online reviews matter? An empirical investigation of panel data, Decision Support Systems, 45, 1007–1016.CrossRefGoogle Scholar
Duan, W., Gu, B., and Whinston, A.B. (2009). Informational cascades and software adoption on the Internet: An empirical investigation, MIS Quarterly, 33(1), 23–48.CrossRefGoogle Scholar
Edwards, S. (2006). From the guest editor: Special issue on electronic word of mouth and its relationship with advertising, marketing, and communication, Journal of Interactive Advertising, 6(2), 1–2.CrossRefGoogle Scholar
Fisher, M., Newman, G.E., and Dhar, R. (2018). Seeing stars: How the binary bias distorts the interpretation of customer ratings, Journal of Consumer Research, 45(3), 471–489.CrossRefGoogle Scholar
Gallagher, S.E. and Savage, T. (2013). Cross-cultural analysis in online community research: A literature review, Computers in Human Behavior, 29(3), 1028–1038.CrossRefGoogle Scholar
Gambetta, D. (2011). Signaling. In Hedstrom, P. and Bearman, P. (eds.), The Oxford Handbook of Analytical Sociology, Oxford University Press.Google Scholar
Ghose, A. and Ipeirotis, P.G. (2011). Estimating the helpfulness and economic impact of product reviews: Mining text and reviewer characteristics, IEEE Transactions on Knowledge and Data Engineering, 23(10), 1498–1512.CrossRefGoogle Scholar
Grewal, L. and Stephen, A. (2019). In mobile we trust: The effects of mobile versus nonmobile reviews on consumer purchase intentions, Journal of Marketing Research, 56(5), 791–808.CrossRefGoogle Scholar
Godes, D. (2017). Product policy in markets with word-of-mouth communication, Management Science, 63(1), 267–278.CrossRefGoogle Scholar
Godes, D. and Mayzlin, D. (2004) Using online conversations to study word of mouth communication, Marketing Science, 23(4), 545–560.CrossRefGoogle Scholar
Godes, D. and Mayzlin, D. (2009) Firm-created word-of-mouth communication: Evidence from a field test, Marketing Science, 28(4), 617–808.CrossRefGoogle Scholar
Godes, D. and Silva, J.C. (2012). Sequential and temporal dynamics of online opinion, Marketing Science, 31(3), 448–473.CrossRefGoogle Scholar
Ho-Dac, N., Carson, S.J., and Moore, W.L. (2013). The effects of positive and negative online customer reviews: Do brand strength and category maturity matter? Journal of Marketing, 77(6), 37–53.CrossRefGoogle Scholar
Hofstede, G. (2010). Cultures and Organizations: Software of the Mind, 3rd ed. McGraw-Hill Education.Google Scholar
Huang, M., Xie, H., Rao, Y., Liu, Y., Poon, L.K.M., and Wang, F.L. (2020). Lexicon-based sentiment convolutional neural networks for online review analysis, IEEE Transactions on Affective Computing, 1–12.Google Scholar
Keller, K. (1993). Conceptualizing, measuring, and managing customer-based brand equity, Journal of Marketing Research, 57(1), 1–22.CrossRefGoogle Scholar
Kim, R.Y. (2019). Does national culture explain consumers’ reliance on online reviews? Cross-cultural variations in the effect of online review ratings on consumer choice, Electronic Commerce Research and Applications, 37, 100878.CrossRefGoogle Scholar
Kim, R.Y. (2020). The influx of skeptics: An investigation of the diffusion cycle effect on online review, Electronic Markets, 30(4), 821–835.CrossRefGoogle Scholar
Kim, R.Y. (2021). When does online review matter to consumers? The effect of product quality information cues, Electronic Commerce Research, 21(4), 1011–1031.CrossRefGoogle Scholar
Kozinets, R.V. (2016). Amazonian forests, and trees: Multiplicity and objectivity in studies of online consumer-generated ratings and reviews. A commentary on de Langhe, Fernbach, and Lichtenstein, Journal of Consumer Research, 42, 834–839.CrossRefGoogle Scholar
Lamberton, C. and Stephen, A. (2016), A thematic exploration of digital, social media, and mobile marketing: Research evolution from 2000 to 2015 and an agenda for future inquiry, Journal of Marketing, 80(6), 146–172.CrossRefGoogle Scholar
Langhe, B.D., Fernbach, P.M., and Lichtenstein, D.R. (2016). Navigating by the stars: Investigating the actual and perceived validity of online user ratings, Journal of Consumer Research, 42(6), 817–833.CrossRefGoogle Scholar
Lee, J., Jung, S., and Park, J. (2017). The role of entropy of review text sentiments on online WOM and movie box office sales, Electronic Commerce Research and Applications, 22, 42–52.CrossRefGoogle Scholar
Lee, J., Park, D., and Han, I. (2008) The Effect of negative online consumer reviews on product attitude: An information processing view, Electronic Commerce Research and Applications, 7(3), 341–352.CrossRefGoogle Scholar
Li, M., Huang, L., Tan, C., and Wei, K. (2013). Helpfulness of online product reviews as seen by consumers: Source and content features, International Journal of Electronic Commerce Research, 17(4), 101–136.CrossRefGoogle Scholar
Liu, Y. (2006). Word of Mouth for movies: Its dynamics and impact on box office revenue, Journal of Marketing, 70(3), 74–89.CrossRefGoogle Scholar
Liu, Q., Zhang, X., Zhang, L., and Zhao, Y. (2019). The interaction effects of information cascades, word of mouth and recommendation systems on online reading behavior: An empirical investigation, Electronic Commerce Research, 19(3), 521–547.CrossRefGoogle Scholar
Luca, M. and Zervas, G. (2016), Fake it till you make it: Reputation, competition, and Yelp review fraud, Management Science, 62 (12), 3412–3427.CrossRefGoogle Scholar
Mayzlin, D. (2006). Promotional chat on the Internet, Marketing Science, 25(2), 155–163.CrossRefGoogle Scholar
Moe, W.W., and Schweidel, D.A. (2011). Online product opinion: Incidence, evaluation, and evolution, Marketing Science, 31(3), 372–386.CrossRefGoogle Scholar
Mudambi, S.M. and Schuff, D. (2010). What makes a helpful online review? A study of customer reviews on Amazon.com, MIS Quarterly, 34(1), 185–200.CrossRefGoogle Scholar
Nickerson, R.S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises, Review of General Psychology, 2(2), 175–220.CrossRefGoogle Scholar
Reichheld, F. (2003). The one number you need to grow, Harvard Business Review, 81(12), 46–54.Google ScholarPubMed
Rook, D.W. and Fisher, R.J. (1995). Normative influences on impulsive buying behavior, Journal of Consumer Research, 22(3), 305–313.CrossRefGoogle Scholar
Roselius, T. (1971). Consumer rankings of risk reductions methods, Journal of Marketing, 35(1), 56–61.CrossRefGoogle Scholar
Simonson, I. (2016). Imperfect progress: An objective quality assessment of the role of user reviews in consumer decision making: A commentary on de Langhe, Fernbach, and Lichtenstein, Journal of Consumer Research, 42, 840–845.CrossRefGoogle Scholar
Smith, A. and Anderson, M. (2016) Online Reviews, Online Shopping and E-Commerce: Pew Research Center, retrieved from www.pewresearch.org/internet/wp-content/uploads/sites/9/2016/12/PI_2016.12.19_Online-Shopping_FINAL.pdf.Google Scholar
Stephen, A.T. (2016), The role of digital and social media marketing in consumer behavior, Current Opinion in Psychology, 10, 17–21.CrossRefGoogle Scholar
Stock, A. and Balachander, S. (2005). The making of a “hot product”: A signaling explanation of marketers’ scarcity strategy, Management Science, 51(8), 1181–1192.CrossRefGoogle Scholar
Trusov, M., Bucklin, R.E., and Pauwels, K. (2009). Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site, Journal of Marketing, 73(5), 90–102.CrossRefGoogle Scholar
Tuk, M.A., Verlegh, P.W., Smidts, A., and Wigboldus, D.H. (2008). Sales and sincerity: The role of relational framing in word of mouth marketing, Journal of Consumer Psychology, 19(1), 38–47.CrossRefGoogle Scholar
van Laer, T.J.E. Escalas, S. Ludwig, E.A. v. Hende, (2019). What happens in Vegas stays on TripAdvisor? A theory and technique to understand narrativity in consumer reviews, Journal of Consumer Research, 46(2), 267–285.Google Scholar
Villanueva, J., Yoo, S., and Hanssens, D.M. (2008). The impact of marketing-induced versus Word-of-Mouth customer acquisition on customer equity growth, Journal of Marketing Research, 45(1), 48–59.CrossRefGoogle Scholar
Wangenheim, F.v. and Bayón, T. (2007). The chain from customer satisfaction via word-of-mouth referrals to new customer acquisition. Journal of the Academy of Marketing Science, 35, 233–249.CrossRefGoogle Scholar
Weathers, D., Sharma, S., and Wood, S.L. (2007). Effects of online communication practices on consumer perceptions of performance uncertainty for search and experience goods, Journal of Retailing, 83(4), 393–401.CrossRefGoogle Scholar
Winer, R.S. and Fader, P.S. (2016). Objective vs. online ratings: Are low correlations unexpected and does it matter? A commentary on de Langhe, Fernbach, and Lichtenstein, Journal of Consumer Research, 42(6), 846–849.CrossRefGoogle Scholar
Womply, (2021). Is it time to consider reputation monitoring services? Retrieved from www.womply.com/blog/time-consider-reputation-monitoring-services.Google Scholar
Woodside, A.G. and Delozier, W.. (1976). Effects of word of mouth advertising on consumer risk taking, Journal of Advertising, 5(4), 12–19.CrossRefGoogle Scholar
Xia, H. Y. Yang, X. Pan, , and Zhang, Z. (2020). Sentiment analysis for online reviews using conditional random fields and support vector machines, Electronic Commerce Research, 20, 343–360.CrossRefGoogle Scholar
Yin, D., Mitra, S., and Zhang, H. (2016). When do consumers value positive vs. negative reviews? An empirical investigation of confirmation bias in online word of mouth, Information Systems Research, 27(1), 131–144.CrossRefGoogle Scholar
You, Y., Vadakkepatt, G., and Joshi, A. (2015). A meta-analysis of electronic Word-of-Mouth elasticity, Journal of Marketing, 79(2), 19–39.CrossRefGoogle Scholar
Yu, X., Liu, Y., Huang, X., and An, A. (2012). Mining online reviews for predicting sales performance: A case study in the movie domain, IEEE Transactions on Knowledge and Data Engineering, 24(4), 720–734.CrossRefGoogle Scholar
Zhao, Y., Yang, S., Narayan, V., and Zhao, Y. (2012). Modeling consumer learning from online product reviews, Marketing Science, 32(1), 153–169.CrossRefGoogle Scholar
Zhou, W. and Duan, W. (2012). Online user reviews, product variety, and the long tail: An empirical investigation on online software downloads, Electronic Commerce Research and Applications, 11(3), 275–289.CrossRefGoogle Scholar
Zhu, F. and Zhang, X. (2010). Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics, Journal of Marketing, 74(2), 133–148.CrossRefGoogle Scholar
References
Blair, S., Claster, P., & Claster, S. 2015. Technology and Youth: Growing Up in a Digital World. Sociological Studies of Children and Youth, Vol. 19. Emerald Group Publishing.CrossRefGoogle Scholar
Broadbent, E., Gougoulis, J., Lui, N., Pota, V., & Simons, J. 2017. Generation Z: Global Citizenship Survey. Available at: www.varkeyfoundation.org/media/4487/global-young-people-report-single-pages-new.pdfGoogle Scholar
Center for Generational Kinetics. 2016. General Breakdown: Info about All of the Generations. Available at: https://genhq.com/faq-info-about-generations/Google Scholar
Chaffey, D. & Ellis-Chadwick, F. 2019. Digital Marketing: Strategy, Implementation and Practice. 7th edition. Pearson Education Limited.Google Scholar
Cheung, C.M.K., Lee, M.K.O., & Rabjohn, N. 2008. The impact of electronic word-of-mouth: The adoption of online opinions in online customer communities. Internet Research, 18 (3), 229–247.CrossRefGoogle Scholar
Chicca, J. & Shellenbarger, T. 2018. Connecting with Generation Z: Approaches in nursing education. Teaching and Learning in Nursing, 13 (3), 181.CrossRefGoogle Scholar
Colicev, A., Kumar, A., & O’Connor, P. 2019. Modeling the relationship between firm and user generated content and the stages of the marketing funnel. International Journal of Research in Marketing, Elsevire, 36(1), 100–116.CrossRefGoogle Scholar
Drury, G. 2008. Should marketers engage and how can it be done effectively? Journal of Direct, Data and Digital Marketing Practice, 9, 274–277.CrossRefGoogle Scholar
Duffett, R. 2017. Influence of social media marketing communications on young consumers’ attitudes. Young Consumers, 18 (1), 19–39.CrossRefGoogle Scholar
Duffett, R. 2020. The YouTube marketing communication effect on cognitive, affective and behavioural attitudes among Generation Z consumers. Sustainability, 12(12), 1–25.CrossRefGoogle Scholar
Dunlop, S., Freeman, B., & Jones, S.J. 2016. Marketing to youth in the digital age: The promotion of unhealthy products and health promoting behaviours on social media. Media and Communication, 4 (3), 35–49.CrossRefGoogle Scholar
Ebrand Group. 2019. Some ja nuoret 2019. Available at: www.ebrand.fi/some-ja-nuoret-2019-tulokset-julkaistuGoogle Scholar
Evans, N., Hoy, M., & Childers, C. 2018. Parenting “YouTube natives”: The impact of pre-roll advertising and text disclosures on parental responses to sponsored child influencer videos. Journal of Advertising, 47, 326–346.CrossRefGoogle Scholar
Fierro, I. & Gavilanez, J. 2017. Digital marketing. Pensamiento & Gestión, 43, 220–240.Google Scholar
Flanagin, A.J. & Metzger, M. 2008. Digital media and youth: Unparalleled opportunity and unprecedented responsibility. Digital Media, Youth, and Credibility, 5–28.Google Scholar
Francis, T. & Hoefel, F. 2018. ‘True Gen’: Generation Z and its implications for companies. Available at: https://innovationinsider.com.br/wp-content/uploads/2019/05/Generation-Z-and-its-implication-for-companies.pdfGoogle Scholar
Gaidhani, S., Arora, L., & Sharma, B.K. 2019. Understanding the attitude of generation Z towards workplace. International Journal of Management, Technology and Engineering, 9 (1), 2804–2812.Google Scholar
Glucksman, M. 2017. The rise of social media influencer marketing on lifestyle branding: A case study of Lucie Fink. Elon Journal of Undergraduate Research in Communications, 8(2), 77–87.Google Scholar
Gupta, O. & Gulati, G. 2014. Psycho-analysis of mobile applications usage among Generation Z teens. International Journal on Global Business Management & Research, 3 (1), 80–95.Google Scholar
Iyengar, R., Han, S., & Gupta, S. 2009. Do Friends Influence Purchases in a Social Network? Harvard Business School Marketing Unit, paper no. 09-123.Google Scholar
Jenkins, R. 2018. Marketing to Generation Z? Here’s What You Need to Know. Available at: www.inc.com/ryan-jenkins/marketing-to-generation-z-heres-what-you-need-to-know.htmlGoogle Scholar
Jin, S.V., Muqaddam, A., & Ruy, E. 2019. Instafamous and social media influencer marketing. Marketing Intelligence & Planning, 37 (5), 567–579.CrossRefGoogle Scholar
Kadekova, Z. & Holiencinova, M. 2018. Influencer marketing as a modern phenomenon creating a new frontier of virtual opportunities. Communication Today, 9(2), 90–105.Google Scholar
Kannan, P.K. & Li, H. 2017. Digital marketing: A framework, review and research agenda. International Journal of Research in Marketing, 34 (1), 22–45.CrossRefGoogle Scholar
Karjaluoto, H. & Mustonen, N. 2015. The role of digital channels in industrial marketing communications. Journal of Business and Industrial Marketing, 30 (6), 703–710.CrossRefGoogle Scholar
Kee, A.W. & Yazdanifard, R. 2015. The review of content marketing as a new trend in marketing practices. International Journal of Management, Accounting and Economics, 2(9), 1055–1064.Google Scholar
Kingsnorth, S. 2016. Digital Marketing Strategy: An Integrated Approach to Online Marketing. Kogan Page Limited.Google Scholar
Kranzler, E. & Bleakley, A. 2019. Youth social media use and health outcomes: #diggingdeeper. Journal of Adolescent Health, 64, 141–142.CrossRefGoogle ScholarPubMed
Lamberton, C. & Stephen, A. 2016. A thematic exploration of digital, social media, and mobile marketing: Research evolution from 2000 to 2015 and an agenda for future inquiry. Journal of Marketing, 80 (6), 146–172.CrossRefGoogle Scholar
Leeflang, P., Verhoef, P., Dahlström, P., & Freundt, T. 2014. Challenges and solutions for marketing in a digital era. European Management Journal, 32, 1–12.CrossRefGoogle Scholar
Liu, X., Hyunju, S., & Burns, A.C. 2019. Examining the impact of luxury brands’ social media marketing on customer engagement: Using big data analytics and natural language processing. Journal of Business Review, 125, 815–826.Google Scholar
Liu, Y. & Ying, X. 2010. Review of Social Network Sites: Definition, Experience and Applications. Proceedings of the Conference on Web Based Business Management, 749–752.Google Scholar
Livingstone, S. 2008. Taking risky opportunities in youthful content creation: Teenagers’ use of social networking sites for intimacy, privacy and self-expression. New Media & Society, 10(3), 393–411.CrossRefGoogle Scholar
Machado, C. & Davim, P. 2016. MBA: Theory and Applications of Business and Management Principles. Springler Science & Business Media.CrossRefGoogle Scholar
Mangold, W.G. & Faulds, D.J. 2009. Social media: The new hybrid element of the promotion mix. Business Horizons, 52(4), 357–365.CrossRefGoogle Scholar
Marketo. 2014. The Definite Guide to Engaging Content Marketing. Available at: https://go.marketo.com/rs/marketob2/images/DG2ECM.pdfGoogle Scholar
Miller, K., Murphrey, T., & Alvis, S. 2018. Harnessing interactive technologies to serve Generation Z. The Agricultural Education Magazine, 85 (1), 5–7.Google Scholar
Naab, T.K. & Sehl, A. 2016. Studies of user generated content: A systematic review. Journalism, 18 (10), 2–37.Google Scholar
Nadaraja, R. & Yazdanifard, R. 2013. Social Media Marketing: Advantages and Disadvantages. Research Gate.Google Scholar
Naz, F. 2014. Word of mouth and its impact on marketing. International Journal of Scientific and Research Publications, 4(1), 1–4.Google Scholar
Needham, Andrew. 2008. Word of mouth, youth and their brands. Young Consumers: Bradford, 9(1), 60–62.CrossRefGoogle Scholar
O’Hern, M. & Kahle, L.N. 2013. The empowered customer: User-generated content and the future of marketing. Global Economics and Management Review, 18, 21–29.CrossRefGoogle Scholar
Omnicore Agengy. 2019a. Facebook by the Numbers: Stats, Demographics and Fun Facts. Available at: www.omnicoreagency.com/facebook-statistics/Google Scholar
Omnicore Agengy. 2019b. Instagram by the Numbers: Stats, Demographics and Fun Facts. Available at: www.omnicoreagency.com/instagram-statistics/Google Scholar
Omnicore Agengy. 2019c. Snapchat by the Numbers: Stats, Demographics and Fun Facts. Available at: www.omnicoreagency.com/snapchat-statistics/Google Scholar
Omnicore Agengy. 2019d. YouTube by the Numbers: Stats, Demographics and Fun Facts. Available at: www.omnicoreagency.com/youtube-statistics/Google Scholar
Omnicore Agency. 2020. TikTok by the Numbers: Stats, Demographics & Fun Facts. Available at: www.omnicoreagency.com/tiktok-statistics/Google Scholar
Östman, J. 2012. Information, expression, participation: How involvement in user-generated content relates to democratic engagement among young people. New Media & Society, 14(6), 1004–1021.CrossRefGoogle Scholar
Peres, P. 2018. Characteristics and Learning Needs of Generation Z. European Conference on e-Learning, 464–473.Google Scholar
PEW Research Center. 2018. Teens, Social Media and Technology 2018. Available at: www.pewresearch.org/internet/2018/05/31/teens-social-media-technology-2018/Google Scholar
Priporas, C-V., Stylos, N., & Fotiadis, A.K. 2017. Generation Z consumers’ expectations of interactions in smart retailing: A future agenda. Computers in Human Behavior, 77, 374–381.CrossRefGoogle Scholar
Roseberry-Mckibbin, C. 2017. Generation Z rising. ASHA Leader: Rockville, 12, 36–38.CrossRefGoogle Scholar
Sandeen, C. 2008. Boomers, Xers, and Millennials: Who are they and what do they really want from continuing higher education? Continuing Higher Education Review, 72, 11–31.Google Scholar
Sharma, R. & Srivastava, D. 2017. Measuring customer response to word-of-mouth messages on social media: Development of a multi-item scale. Journal of Creative Communications, 12(3), 185–204.CrossRefGoogle Scholar
Shatto, B. & Erwin, K. 2016. Moving on from Millennials: Preparing for Generation Z. The Journal of Continuing Education in Nursing, 47 (6), 253–254.CrossRefGoogle ScholarPubMed
Smith, A.N., Fischer, E., & Yongjian, C. 2012. How does brand-related user-generated content differ across YouTube, Facebook, and Twitter? Journal of Interactive Marketing, 26, 102–113.CrossRefGoogle Scholar
Southgate, D. 2017. The emergence of Generation Z and its impact in advertising: Long-term implications for media planning and creative development. Journal of Advertising Research, 57 (2), 227–235.CrossRefGoogle Scholar
Stackla. 2019. The Consumer Content Report: Influence in the Digital Age. Available at: https://stackla.com/resources/reports/the-consumer-content-report-influence-in-the-digital-age/Google Scholar
Statista. 2018. Teen’s Social Media Usage is Drastically Increasing. Available at: www.statista.com/chart/15720/frequency-of-teenagers-social-media-use/Google Scholar
Swanzen, R. 2016. Facing the generation chasm: The parenting and teaching of Generations Z and Y. International Journal of Child, Youth and Family Studies, 9 (2), 125–150.CrossRefGoogle Scholar
Tiago, M. & Verissimo, J. 2014. Digital marketing and social media: Why bother? Business Horizons, 57, 703–708.CrossRefGoogle Scholar
Torlak, O., Ozkara, B., Tiltay, M., Cengiz, H., & Dulger, M. 2014. The effect of electronic word of mouth on brand image and purchase intention: An application concerning cell phone brands for youth consumers in Turkey. Journal of Marketing Development and Competitiveness, 8(2), 61–68.Google Scholar
Tulgan, B. 2013. Meet Generation Z: The second generation within the giant “Millennial” cohort. Available at: https://grupespsichoterapija.lt/wp-content/uploads/2017/09/Gen-Z-Whitepaper.pdfGoogle Scholar
Turner, A. 2015. Generation Z: Technology and social interest. The Journal of Individual Psychology, 71 (2), 103–113.CrossRefGoogle Scholar
Vetter, A. 2017. Managing Generation Z: These digital natives are surprisingly like Baby Boomers. Accounting Today, 31 (7), 28–31.Google Scholar
Viestintäliiga. 2019. Some ja nuoret 2019. Available at: https://viestintaliiga.fi/some-ja-nuoret-2019/Google Scholar
Wee, V. 2017. Youth audiences and the media in the digital era: The intensification of multimedia engagement and interaction. Cinema Journal Fall, 57 (1), 133–139.CrossRefGoogle Scholar
Williams, A. 2015. Move Over, Millennials, Here Comes Generation Z. Available at: www.nytimes.com/2015/09/20/fashion/move-over-millennials-here-comes-generation-z.htmlGoogle Scholar
Wood, S. 2013. Generation Z as Consumers: Trends and Innovation. Institute for Emerging Issues: NC State University.Google Scholar
Xiao, M., Wang, R., & Chan-Olmsted, S. 2018. Factors affecting YouTube influencer marketing credibility: A heuristic-systematic model. Journal of Media Business Studies, 1–26.Google Scholar
Yang, Y. & Coffey, A. 2014. Audience valuation in the new media era: Interactivity, online engagement, and electronic word-of-mouth value. The International Journal on Media Management, 16, 77–113.CrossRefGoogle Scholar
Yurdakul-Şahin, D. & Atik, D. 2013. Celebrity influences on young consumers: Guiding the way to the ideal self. Izmir Review of Social Sciences, 1(1), 65–82.Google Scholar
References
Abeysekera, L., & Dawson, P. (2015). Motivation and cognitive load in the flipped classroom: Definition, rationale and a call for research. Higher Education Research and Development, 34(1), 1–14. https://doi.org/10.1080/07294360.2014.934336CrossRefGoogle Scholar
Aggarwal, P. & O’Brien, C. L. (2008) Social loafing on group projects: Structural antecedents and effect on student satisfaction. Journal of Marketing Education, 30(3), 255–64. http://doi.org/10.1177/0273475308322283CrossRefGoogle Scholar
Algarni, A., & Burd, L. (2015). Perceptions of students and instructors toward the role of CommEasy in tackling communication and interaction barriers in distance-learning classrooms. In Proceedings of the 2015 IEEE Frontiers in education conference (FIE ’15). IEEE Computer Society. https://doi.org/10.1109/FIE.2015.7344130Google Scholar
Alvídrez, S., Piñeiro-Naval, V., Marcos-Ramos, M., & Rojas-Solís, J. L. (2015). Intergroup contact in computer-mediated communication: The interplay of a stereotype-disconfirming behavior and a lasting group identity on reducing prejudiced perceptions. Computers in Human Behavior, 52, 533–540. https://doi.org/10.1016/j.chb.2014.09.006CrossRefGoogle Scholar
Anderson, T., & Dron, J. (2011). Three generations of distance education pedagogy. International Review of Research in Open and Distance Learning, 12(3), 80–97. https://doi.org/10.19173/irrodl.v12i3.890CrossRefGoogle Scholar
Bagherian, F., & Thorngate, W. (2000). Horses to water: Student use of course newsgroups. FirstMonday, 5(8). https://doi.org/10.5210/fm.v5i8.779Google Scholar
Baker, M., & Lund, K. (1997). Promoting reflective interactions in a CSCL environment. Journal of Computer Assisted Learning, 13(3), 175–193. https://doi.org/10.1046/j.1365-2729.1997.00019.xCrossRefGoogle Scholar
Bales, R. F. (1965) The equilibrium problem in small groups. In Hare, A. P., Borgatta, E. F., & Bales, R. F. (Eds.), Small groups: Studies in social interaction. Knopf.Google Scholar
Bodemer, D., & Dehler, J. (2011). Group awareness in CSCL environments. Computers in Human Behavior, 27(3), 1043–1045. https://doi.org/10.1016/j.chb.2010.07.014CrossRefGoogle Scholar
Boekaerts, M., & Pekrun, R. (2016). Emotions and emotion regulation in academic settings. In Corno, L., & Anderman, E. M. (Eds), Handbook of educational psychology (3rd ed., pp. 76–90). Routledge.Google Scholar
Bolliger, D. U., & Halupa, C. (2012). Student perceptions of satisfaction and anxiety in an online doctoral program. Distance Education, 33(1), 81–98. https://doi.org/10.1080/01587919.2012.667961CrossRefGoogle Scholar
Bonebright, D. A. (2010). Perspectives. 40 years of storming: A historical review of Tuckman’s model of small group development. Human Resource Development International, 13(1), 111–120. https://doi.org/10.1080/13678861003589099CrossRefGoogle Scholar
Bowen, C. W. (2000). A quantitative literature review of cooperative learning effects on high school and college chemistry achievement. Journal of Chemical Education, 77(1), 116–119. https://doi.org/10.1021/ed077p116CrossRefGoogle Scholar
Bowers, J., & Kumar, P. (2015). Students’ perceptions of teaching and social presence: A comparative analysis of face-to-face and online learning environments. International Journal of Web-Based Learning and Teaching Technologies, 10(1), 27–44. https://doi.org/10.4018/978-1-5225-0783-3.ch073CrossRefGoogle Scholar
Bromme, R., Hesse, F. W., Spada, H. (Eds.). (2005). Barriers and biases in computer-mediated knowledge communication: And how they may be overcome (Vol. 5). Springer Science+Business Media.CrossRefGoogle Scholar
Chandrasekaran, S., Badwal, P. S., Littlefair, G., & Mühlfelder, M. (2016). Framework guidelines for students: Collaborative learning in distance education. Journal of Modern Education Review, 6(12), 940–951. https://doi.org/10.15341/jmer(2155-7993)/12.06.2016/008Google Scholar
Chauhan, J. (2017). An insight to collaboration in MOOC. International Journal of Advance Engineering and Research Development, 4(7), 82–90. https://doi.org/10.21090/IJAERD.21579Google Scholar
Clark, H. H., & Brennan, S. E. (1991). Grounding in communication. In Resnick, L. B., Levine, J. M., & Teasley, S. D. (Eds.), Perspectives on socially shared cognition (pp. 127–149). American Psychological Association. https://doi.org/10.1037/10096-006CrossRefGoogle Scholar
Comer, D. R. (1995). A model of social loafing in real work groups. Human Relations, 48(6), 647–667. https://doi.org/10.1177/001872679504800603CrossRefGoogle Scholar
Cui, G., Lockee, B., & Meng, C. (2013). Building modern online social presence: A review of social presence theory and its instructional design implications for future trends. Education and Information Technologies, 18(4), 661–685. https://doi.org/10.1007/s10639-012-9192-1CrossRefGoogle Scholar
Day, S. P., & Bryce, T. G. K. (2013). The benefits of cooperative learning to socio-scientific discussion in secondary school science. International Journal of Science Education, 35(9), 1533–1560, https://doi.org/10.1080/09500693.2011.642324CrossRefGoogle Scholar
De Jong, F. (2019). Kennis in-(ter)-actie: Responsief leren als kennis constructie. Inaugural address. Heerlen, The Netherlands. Open University of the Netherlands.CrossRefGoogle Scholar
De Lima, D. P. R., Gerosa, M. A., & Conte, T.U (2019). What to expect, and how to improve online discussion forums: The instructors’ perspective. Journal of Internet Services and Applications, 10(22). https://doi.org/10.1186/s13174-019-0120-0CrossRefGoogle Scholar
Dillenbourg, P. (1999). What do you mean by “collaborative learning”? In Dillenbourg, P. (Ed.), Collaborative learning: Cognitive and computational approaches (pp. 1–16). Pergamon, Elsevier Science.Google Scholar
Dillenbourg, P. (2002). Over-scripting CSCL: The risks of blending collaborative learning with instructional design. In Kirschner, P. A. (Ed.), Three worlds of CSCL: Can we support CSCL (pp. 61–91). Open Universiteit Nederland.Google Scholar
Dillenbourg, P., & Jermann, P. (2007), Designing integrative scripts. In Fischer, F., Kollar, I.., Mandl, H., & Haake, J. M. (Eds.), Scripting computer-supported collaborative learning: Cognitive, computational and educational perspectives (Vol. 6, pp. 275–301). Springer.CrossRefGoogle Scholar
Dumford, A. D., & Miller, A. L. (2018). Online learning in higher education: Exploring advantages and disadvantages for engagement. Journal of Computing in Higher Education, 30, 452–465. https://doi.org/10.1007/s12528-018-9179-zCrossRefGoogle Scholar
Erichsen, E. A., & Bolliger, D. U. (2011). Towards understanding international graduate student isolation in traditional and online environments. Educational Technology Research and Development, 59, 309–326. https://doi.org/10.2307/41414943CrossRefGoogle Scholar
Ertl, B., Kopp, B., & Mandl, H. (2007). Supporting collaborative learning in videoconferencing using collaboration scripts and content schemes. In Fischer, F., Kollar, I., Mandl, H., & Haake, J. M. (Eds.), Scripting computer-supported collaborative learning (Vol. 6, pp. 213–236). Springer.CrossRefGoogle Scholar
Exter, M. E., Korkmaz, N., Harlin, N. M., & Bichelmeyer, B. A. (2009). Sense of community within a fully online program: Perspective of graduate students. The Quarterly Review of Distance Education, 10(20), 177–194.Google Scholar
Finntrack Ltd. (2011). Group development. Available at: http://finntrack.co.uk/leadership/people_and_org/grp8.htmGoogle Scholar
Fischer, F., Bruhn, J., Gräsel, C., & Mandl, H. (2002) Fostering collaborative knowledge construction with visualization tools. Learning and Instruction, 12, 213–232. https://doi.org/10.1016/S0959-4752(01)00005-6CrossRefGoogle Scholar
Fischer, F., Kollar, I., Stegmann, K., & Wecker, C., (2013). Toward a script theory of guidance in computer-supported collaborative learning. Educational Psychologist, 48(1), 56–66. https://doi.org/10.1080/00461520.2012.748005CrossRefGoogle Scholar
Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: The reasoned action approach. Psychology Press. doi: 10.4324/9780203838020Google Scholar
Fransen, J., Weiberger, A., & Kirschner, P. A. (2013). Team effectiveness and team development in CSCL. Educational Psychologist, 48(1), 9–24. https://doi.org/10.1080/00461520.2012.747947CrossRefGoogle Scholar
Gabbert, B., Johnson, D. W., Johnson, R. T. (1986). Cooperative learning, group-to-individual transfer, process gain, and the acquisition of cognitive reasoning strategies. Journal of Psychology Interdisciplinary and Applied, 120(3), 265–278. https://doi.org/10.1080/00223980.1986%20.10545253CrossRefGoogle Scholar
Garrison, D. R. (1993). Quality and theory in distance education: Theoretical consideration. In Keegan, D. (Ed.), Theoretical principles of distance education. Routledge.Google Scholar
Ghaffari, M. (2019). Building a community of learners: Lessons learned. Nursing Practice and Health Care, 1(1), 1–7.Google Scholar
Gilbert, L., & Moore, D. R. (1998). Building interactivity into web-courses: Tools for social and instructional interaction. Educational Technology, 38(3), 29–35.Google Scholar
Gillies, R. M. (2003). Structuring cooperative group work in classrooms. International Journal of Educational Research, 39, 35–49. https://doi.org/10.1016/S0883-0355(03)00072-7CrossRefGoogle Scholar
Gillies, R. M., & Ashman, A. F. (1996). Teaching collaborative skills to primary school children in classroom-based work groups. Learning and Instruction, 6(3), 187–200. https://doi.org/10.1016/0959-4752(96)00002-3CrossRefGoogle Scholar
Gillies, R. M., & Ashman, A. F. (1998). Behavior and interactions of children in cooperative groups in lower and middle elementary grades. Journal of Educational Psychology, 90(4), 746–757. https://doi.org/10.1037/0022-0663.90.4.746CrossRefGoogle Scholar
Goodwin, M. W. (1999). Cooperative learning and social skills: What skills to teach and how to teach them. Intervention in School and Clinic, 35(1), 29–33. https://doi.org/10.1177/105345129903500105CrossRefGoogle Scholar
Goodyear, P., & Zenios, M. (2007). Discussion, collaborative knowledge work and epistemic fluency. British Journal of Educational Studies, 55, 351–368. https://doi.org/https://doi.org/10.1111/j.1467-8527.2007.00383.xCrossRefGoogle Scholar
Greene, J. A., & Azevedo, R. (2007). A theoretical review of Winne and Hadwin’s model of self-regulated learning: New perspectives and directions. Review of Educational Research, 77(3), 334–372. https://doi.org/10.3102/003465430303953CrossRefGoogle Scholar
Griffin, P., & Care, E. (Eds.). (2015). Assessment and teaching of 21st century skills: Methods and approach. Springer. https://doi.org/10.1007/978-94-017-9395-7CrossRefGoogle Scholar
Gunawardena, C. N. (1995). Social presence theory and implications for interaction and collaborative learning in computer conferences. International Journal of Educational Telecommunications, 1(2&3), 147–166.Google Scholar
Gunawardena, C. N., Lowe, C. A., & Anderson, T. (1997). Analysis of a global online debate and the development of an interaction analysis model for examining social construction of knowledge in computer conferencing. Journal of Educational Computing Research, 17(4), 397–431. https://dxo.org/10.2190/7MQV-X9UJ-C7Q3-NRAGCrossRefGoogle Scholar
Gunawardena, C. N., and Zittle, F. J. (1997). Social presence as a predictor of satisfaction within a computer-mediated conferencing environment. American Journal of Distance Education, 11, 8–26. https://doi.org/10.1080/08923649709526970CrossRefGoogle Scholar
Gweon, G., Jain, M., McDonough, J., Raj, B., & Rosé, C. P. (2013). Measuring prevalence of other-oriented transactive contributions using an automated measure of speech style accommodation. International Journal of Computer Supported Collaborative Learning, 8(2), 245–265. https://doi.org/10.1007/s11412-013-9172-5CrossRefGoogle Scholar
Hadwin, A. F., Jarvela, S., & Miller, M. (2018). Self-regulation, co-regulation and shared regulation in collaborative learning environments. In Schunk, D. & Greene, J. (Eds.), Handbook of self-regulation of learning and performance (2nd ed., pp. 83–106). Routledge.Google Scholar
Hall, D., & Buzwell, S. (2012). The problem of free-riding in group projects: Looking beyond social loafing as reason for non-contribution. Active Learning Higher Education, 14(1), 37–49. https://doi.org/10.1177/1469787412467123CrossRefGoogle Scholar
Hannafin, R. D., & Foshay, W. R. (2008). Computer-based instruction’s (CBI) rediscovered role in K-12: An evaluation case study of one high school’s use of CBI to improve pass rates on high-stakes tests. Educational Technology Research & Development, 56(2), 147–160. https://doi.org/10.1007/s11423-006-9007-4CrossRefGoogle Scholar
Hillman, D. C., Willis, D. J., & Gunawardena, C. N. (1994). Learner–interface interaction in distance education: An extension of contemporary models and strategies for practitioners. American Journal of Distance Education, 8(2), 30–42. https://doi.org/10.1080/08923649409526853CrossRefGoogle Scholar
Hiltz, S. R. (1990). Evaluating the virtual classroom. In Harasim, L. (Ed.), Online education: Perspectives on a new environment (pp. 133–183). Praeger/Greenwood.Google Scholar
Hobaugh, C. F. (1997). Interactive strategies for collaborative learning. In Olgren, C. (Ed.), Proceedings of the Annual Conference on Distance Teaching and Learning: Competition–Connection–Collaboration (pp. 121–125). University of Wisconsin–Madison.Google Scholar
Hogg, M. A. (2016) Social Identity Theory. In: McKeown, S., Haji, R., Ferguson, N. (Eds.), Understanding peace and conflict through social identity theory. Peace Psychology Book Series. Springer, Cham. https://doi.org/10.1007/978-3-319-29869-6_1Google Scholar
Hong, H. Y., & Sullivan, F. R. (2009). Towards an idea-centered, principle-based design approach to support learning as knowledge creation. Educational Technology Research and Development, 57(5), 613–627. https://doi.org/10.1007/sl1423-009-9122-0CrossRefGoogle Scholar
Hurme, T-R., Merenluoto, K., & Järvelä, S. (2009). Socially shared metacognition of pre-service primary teachers in a computer-supported mathematics course and their feelings of task difficulty: A case study. Educational Research and Evaluation, 15(5), 503–524. https://doi.org/10.1080/13803610903444659CrossRefGoogle Scholar
Hurst, B., Wallace, R., & Nixon, S. B. (2013). The impact of social interaction on student learning. Reading Horizons: A Journal of Literacy and Language Arts, 52(4). Available from https://scholarworks.wmich.edu/reading_horizons/vol52/iss4/5Google Scholar
Iiskala, T., Vauras, M., Lehtinen, E., & Salonen, P. (2011). Socially shared metacognition of dyads of pupils in collaborative mathematical problem-solving processes. Learning and Instruction, 21(3), 379–393. https://doi.org/10.1016/j.learninstruc.2010.05.002CrossRefGoogle Scholar
Isohätälä, J., Järvenoja, H., & Järvelä, S. (2017). Socially shared regulation of learning and participation in social interaction in collaborative learning. International Journal of Educational Research, 81, 11–24. https://doi.org/10.1016/j.ijer.2016.10.006CrossRefGoogle Scholar
Isohätälä, J., Näykki, P., Järvelä, S., & Baker, M. J. (2018). Striking a balance: Socio-emotional processes during argumentation in collaborative learning interaction. Learning, Culture and Social Interaction, 16, 1–19. https://doi.org/10.1016/j.lcsi.2017.09.003CrossRefGoogle Scholar
Järvelä, S., & Hadwin, A. F. (2013). New frontiers: Regulating learning in CSCL. Educational Psychologist, 48(1), 25–39. https://doi.org/10.1080/00461520.2012.748006CrossRefGoogle Scholar
Järvelä, S., Kirschner, P. A., Panadero, E., Malmberg, J., Phielix, C., Jaspers, J., … & Järvenoja, H. (2015). Enhancing socially shared regulation in collaborative learning: Designing for CSCL regulation tools. Educational Technology Research and Development, 63(1), 125–142. http://doi.org/10.1007/s11423-014-9358-1CrossRefGoogle Scholar
Järvenoja, H., & Järvelä, S. (2009). Emotion control in collaborative learning situations: Do students regulate emotions evoked by social challenges? British Journal of Educational Psychology, 79(3), 463–481. https://doi.org/10.1348/000709909X402811CrossRefGoogle ScholarPubMed
Järvenoja, H., & Järvelä, S. (2013). Regulating emotions together for motivated collaboration. In Baker, M., Järvelä, S., & Andriessen, J. (Eds.), Affective learning together (pp. 162–181). Routledge.Google Scholar
Järvenoja, H., Järvelä, S., Törmänen, T., Näykki, P., Malmberg, J. Kurki, K., … Isohätälä, J. (2018). Capturing motivation and emotion regulation during a learning process. Frontline Learning Research, 6(3), 85–104. http://doi.org/10.14786/flr.v6i3.369CrossRefGoogle Scholar
Järvelä, S., Malmberg, J., & Koivuniemi, M. (2016). Recognizing socially shared regulation by using the temporal sequences of online chat and logs in CSCL. Learning and Instruction, 42, 1–11. https://doi.org/10.1016/j.learninstruc.2015.10.006CrossRefGoogle Scholar
Järvenoja, H., Näykki, P. & Törmänen, T. (2019). Emotional regulation in collaborative learning: When do higher education students activate group level regulation in the face of challenges? Studies in Higher Education, 44(10), 1747–1757. https://doi.org/10.1080/03075079.2019%20.1665318CrossRefGoogle Scholar
Järvenoja, H., Volet, S., & Järvelä, S. (2012). Regulation of emotions in socially challenging learning situations: An instrument to measure the adaptive and social nature of the regulation process. Educational Psychology, 33, 31–58. https://doi.org/10.1080/01443410.2012.742334CrossRefGoogle Scholar
Jeong, H., & Hmelo-Silver, C. E. (2010, June). An overview of CSCL methodologies. In Gomez, K., Lyons, L., & Radinsky, J. (Eds.), Proceedings of the 9th International Conference of the Learning Sciences: Vol. 1 (pp. 921–928). International Society of the Learning Sciences.Google Scholar
Johnson, D. W., & Johnson, F. (2017). Joining together: Group theory and group skills (12th ed.). Allyn & Bacon.Google Scholar
Johnson, D. W., & Johnson, R. T. (1988). Critical thinking through structured controversy. Educational Leadership, 45(8), 58–64.Google Scholar
Johnson, D. W., & Johnson, R. T. (2008). Social interdependence theory and cooperative learning: The teacher’s role. In Gillies, R. M., Ashman, A. F., & Terwel, J. (Eds.), The teacher’s role in implementing cooperative learning in the classroom (Vol. 7, pp. 9–37). Springer.CrossRefGoogle Scholar
Johnson, D. W., & Johnson, R. T. (2009). An educational psychology success story: Social inter-dependence theory and cooperative learning. Educational Researcher, 38(5), 365–379. https://doi.org/10.3102/0013189X09339057CrossRefGoogle Scholar
Johnson, D. W., & Johnson, R. T. (2014). Cooperative learning in the 21st century. Anales de Psicología, 30(3), 841–851. https://doi.org/10.6018/analesps.30.3.201241CrossRefGoogle Scholar
Johnson, D. W., & Johnson, R. T. (2017, September, 22–23). Cooperative learning. Paper presented at the Innovación educación: I congreso internacional. Zaragoza, Spain.Google Scholar
Johnson, D. W., & Johnson, R. T. (2018). Cooperative learning: The foundation for active learning. In Brito, S. M. (Ed.), Active learning – Beyond the future (pp. 59–70). IntechOpen. https://doi.org/10.5772/intechopen.81086Google Scholar
Johnson, D. W., Johnson, R. T., & Smith, K. A. (2014). Cooperative learning: Improving university instruction by basing practice on validated theory [Special focus issue: Small-group learning in higher education – Cooperative, collaborative, problem-based, and team-based learning]. Journal on Excellence in College Teaching, 25(3–4), 85–118.Google Scholar
Johnson, D. W., Johnson, R. T., & Stanne, M. B. (2000). Cooperative learning methods: A meta-analysis. Cooperative Learning Center at the University of Minnesota. Available at: www.clcrc.com/pages/cl-methhods.htmlGoogle Scholar
Jonassen, D. H., & Kwon, H. (2001). Communication patterns in computer mediated versus face-to-face group problem solving. Educational Technology Research and Development, 49(1), 35–51.CrossRefGoogle Scholar
Karlin, M., & Ozogul, G. O. (2018). Design and implementation of a structured academic controversy for preservice teachers in a computer education licensure program. Journal of Applied Instructional Design, 7(1), 27–33. https://doi.org/10.28990/jaid2018.071005Google Scholar
Kaye, A. R. (1992). Learning apart together. In Kaye, A. R. (Ed.), Collaborative learning through computer conferencing: The Najaden papers (pp. 1–24). Springer-Verlag.CrossRefGoogle Scholar
Kear, K. (2010, May 3–4). Social presence in online learning communities. In Dirckinck-Holmfeld, L., Hodgson, V., Jones, C., de Laat, M., McConnell, D., & Ryberg, T. (Eds.), Proceedings of the 7th international conference on networked learning 2010 (NLC2010) (pp. 541–548). Aalborg.Google Scholar
Kerr, N. L., & Bruun, S. E. (1981). Ringelmann revisited: Alternative explanations for the social loafing effect. Personality and Social Psychology Bulletin, 7, 224–231.CrossRefGoogle Scholar
Kerr, N. L., & Bruun, S. E. (1983). The dispensability of member effort and group motivation losses: Free-rider effects. Journal of Educational Computing Research, 5, 1–15.Google Scholar
Kirschner, P. A. (2001). Using integrated electronic environments for collaborative teaching/learning. Learning and Instruction, 10(1), 1–9. https://doi.org/10.1016/S0959-4752(00)00021-9CrossRefGoogle Scholar
Kirschner, P. A., Kreijns, K., Phielix, C., & Fransen, J. (2015). Awareness of cognitive and social behaviour in a CSCL environment. Journal of Computer Assisted Learning, 31(1), 59–77. https://doi.org/10.1111/jcal.12084CrossRefGoogle Scholar
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86. https://doi.org/10.1207/s15326985ep4102_1CrossRefGoogle Scholar
Koedinger, K., & Aleven, V. (2007). Exploring the assistance dilemma in experiments with cognitive tutors. Educational Psychology Review, 19(3), 239–264. doi: 10.1007/s10648-007-9049-0CrossRefGoogle Scholar
Kollar, I., Fischer, F., & Hesse, F. W. (2006). Collaboration scripts: A conceptual analysis. Educational Psychology Review, 18(2), 159–185. https://doi.org/10.1007/s10648-006-9007-2CrossRefGoogle Scholar
Koschmann, T. (Ed.). (1996). CSCL: Theory and practice of an emerging paradigm. Lawrence Erlbaum.Google Scholar
Kreijns, K., Kirschner, P. A., & Jochems, W. (2003, August, 26–30). Affording sociability for distributed teamwork: Trials and tribulations. Presentation at the 10th European conference for Research on Learning and Instruction (EARLI). Padova, Italy.Google Scholar
Kreijns, K., Kirschner, P. A., Van Buuren, H., & Jochems, W. (2004). Determining sociability, social space and social presence in (a)synchronous collaborative groups. Cyberpsychology & Behavior, 7(2), 155–172. https://doi.org/10.1089/109493104323024429CrossRefGoogle Scholar
Kreijns, K., Kirschner, P. A., & Vermeulen, M. (2013). Social aspects of CSCL environments: A research framework. Educational Psychologist, 48(4), 229–242. https://doi.org/10.1080/00461520.2012.750225CrossRefGoogle Scholar
Kreijns, K., Xu, K. Weidlich, J. (2021). Social presence: Conceptualization and measurement. Educational Psychology Review. Open Access. https://doi.org/10.1007/s10648-021-09623-8CrossRefGoogle Scholar
Kulik, C.-L. C., & Kulik, J. A. (1991). Effectiveness of computer-based instruction: An updated analysis. Computers in Human Behavior, 7(1), 75–94. https://doi.org/10.1016/0747-5632(91)90030-5CrossRefGoogle Scholar
Laal, M., & Ghodsi, S. M. (2012). Benefits of collaborative learning. Procedia – Social and Behavioral Sciences, 31, 486–490. https://doi.org/10.1016/j.sbspro.2011.12.091CrossRefGoogle Scholar
Lämsä, J., Hämäläinen, R., Koskinen, P., Viiri, J., & Mannonen, J. (2020). The potential of temporal analysis: Combining log data and lag sequential analysis to investigate temporal differences between scaffolded and non-scaffolded group inquiry-based learning processes. Computers & Education, 143, https://doi.org/10.1016/j.compedu.2019.103674CrossRefGoogle Scholar
Le, H., Janssen, J., & Wubbels, T. (2018) Collaborative learning practices: Teacher and student perceived obstacles to effective student collaboration. Cambridge Journal of Education, 48(1), 103–122. https://doi.org/10.1080/0305764X.2016.1259389CrossRefGoogle Scholar
Lee, Y-H. (2015). Facilitating critical thinking using the C-QRAC collaboration script: Enhancing science reading literacy in a computer-supported collaborative learning environment. Computers & Education, 88, 182–191. https://doi.org/10.1016/j.compedu.2015.05.004CrossRefGoogle Scholar
Legon, R., & Garrett, R. (2018). The changing landscape of online learning. A deeper dive. The Changing Landscape of Online Education (The Education Report). Available at: www.qualitymatters.org/sites/default/files/research-docs-pdfs/2018-QM-Eduventures-CHLOE-2-Report.pdfGoogle Scholar
Lethinen, E., Hakkarainen, K., Lipponen, L., Rahikainen, M., & Muukonen, H. (1999). Computer supported collaborative learning: A review of CL-Net Project (The J. H. G. I. Giesbers Reports on Education No. 10). Nijmegen, The Netherlands: University of Nijmegen.Google Scholar
Liaw, S., & Huang, H. (2000). Enhancing interactivity in web-based instruction: A review of the literature. Educational Technology, 40(3), 41–45.Google Scholar
Liberman, N., Sagristano, M. D., & Trope, Y. (2002). The effect of temporal distance on level of mental construal. Journal of Experimental Social Psychology, 38(6), 523–534. https://doi.org/10.1016/S0022-1031(02)00535-8CrossRefGoogle Scholar
Linnenbrink-Garcia, L., & Pekrun, R. (2011). Students’ emotions and academic engagement: Introduction to the special issue. Contemporary Educational Psychology, 36(1), 1–3. https://doi.org/10.1016/j.cedpsych.2010.11.004CrossRefGoogle Scholar
Lipponen, L., Hakkarainen, K., & Paavola, S. (2004). Practices and orientations of CSCL. In Strijbos, J. W., Kirschner, P. A., & Martens, R. L. (Eds.), What we know about CSCL in higher education (pp. 31–51). Kluwer.CrossRefGoogle Scholar
Livingstone, D., & Lynch, K. (2002). Group project work and student-centred active learning: Two different experiences. Journal of Geography in Higher Education, 26(2), 325–345. https://doi.org/10.1080/03098260220144748Google Scholar
Malmberg, J., Järvelä, S., Holappa, J., Haataja, E., Huang, X., & Siipo, A. (2018). Going beyond what is visible: What multichannel data can reveal about interaction in the context of collaborative learning. Computers and Human Behavior, 96, 235–245. https://doi.org/10.1016/j.chb.2018.06.030CrossRefGoogle Scholar
Malmberg, J., Järvelä, S., Järvenoja, H., & Panadero, E. (2015). Promoting socially shared regulation of learning in CSCL: Progress of socially shared regulation among high- and low-performing groups. Computers in Human Behavior, 52, 562–572. https://doi.org/10.1016/j.chb.2015.03.082CrossRefGoogle Scholar
Márquez, L. M. T., Llinás, J. G., & Macías, F. S. (2017). Collaborative learning: Use of the jigsaw technique in mapping concepts of physics. Problems of Education in the 21st Century, 75(1), 92–101.CrossRefGoogle Scholar
McWhaw, K., Schnackenberg, H., Sclater, J., & Abrami, P. C. (2013). From co-operation to collaboration: Helping students become collaborative learners. In Gillies, R. M. & Ashman, A. F. (Eds.), Co-operative learning: The social and intellectual outcomes of learning in groups (pp. 69–86). Routledge Falmer.Google Scholar
Miles, J. R., & Kivlighan, D. M., Jr. (2012). Perceptions of group climate by social identity group in intergroup dialogue. Group Dynamics: Theory, Research, and Practice, 16(3), 189–205. https://doi.org/10.1037/a0028634CrossRefGoogle Scholar
Miller, D. L. (2003). The stages of group development: A retrospective study of dynamic team processes. Canadian Journal of Administrative Sciences, 20(2), 121–134. https://doi.org/10.1111/j.1936-4490.2003.tb00698.xCrossRefGoogle Scholar
Miller, M., & Hadwin, A. (2015). Scripting and awareness tools for regulating collaborative learning: Changing the landscape of support in CSCL. Computers in Human Behavior, 52, 573–588. https://doi.org/0.1016/j.chb.2015.01.050CrossRefGoogle Scholar
Millis, B. J., & Cottell, P. G. (1998) Cooperative learning for higher education faculty. Oryx Press.Google Scholar
Molenaar, I. (2014). Advances in temporal analysis in learning and instruction. Frontline Learning Research, 2(4), 15–24. https://doi.org/10.14786/flr.v2i4.118Google Scholar
Molenaar, I., Sleegers, P., & van Boxtel, C. (2014). Metacognitive scaffolding during collaborative learning: A promising combination. Metacognition and Learning, 9(3), 309–332. https://doi.org/10.1007/s11409-014-9118-yCrossRefGoogle Scholar
Moore, M. G. (1993). Theory of transactional distance. In Keegan, D. (Ed.), Theoretical principles of distance education (pp. 22–38). Routledge.Google Scholar
Moore, M. G. (2019). The theory of transactional distance. In Moore, M. G. & Diehl, W. C. (Eds.), Handbook of distance education (4th ed., pp. 32–46). Routledge.Google Scholar
Morrison, D., & Collins, A. (1996). Epistemic fluency and constructivist learning environments. In Wilson, B. (Ed.), Constructivist learning environments (pp. 107–119). Educational Technology Press.Google Scholar
Mu, J. Stegman, K. & Fisher, F. (2013). How collaboration scripts are internalized: A script theory of guidance perspective. In Rummel, N., Kapur, M., Nathan, M., & Puntambekar, S. (Eds.), To see the world and a grain of sand: Learning across levels of space, time, and scale: CSCL 2013 conference proceedings (Vol. 2): Short papers, panels, posters, demos & community events (pp. 113–116). ISLS.Google Scholar
Muilenburg, L. Y., & Berge, Z. L. (2005). Student barriers to online learning: A factor analytic study. Distance Education, 26(1), 29–48. https://doi.org/10.1080/01587910500081269CrossRefGoogle Scholar
Newberry, B. (2001). Raising student social presence in online classes. In WebNet 2001. Proceedings of the World conference on the WWW and Internet. AACE.Google Scholar
Norman, E., Tjomsland, H. E., & Huegel, D. (2016). The distance between us: Using construal level theory to understand interpersonal distance in a digital age. Frontiers in Digital Humanities, 3, 5. https://doi.org/10.3389/fdigh.2016.00005CrossRefGoogle Scholar
Noroozi, O., Weinberger, A., Biemans, H. J. A., Mulder, M., & Chizari, M. (2013). Facilitating argumentative knowledge construction through a transactive discussion script in CSCL. Computers & Education, 61, 59–76. https://doi.org/10.1016/j.compedu.2012.08.013CrossRefGoogle Scholar
Northrup, P. T. (2001). A framework for designing interactivity into web-based instruction. Educational Technology, 41(2), 31–39.Google Scholar
OECD: PISA 2015. (2017). Results (Volume V): Collaborative problem polving. OECD Publishing.Google Scholar
Ohlsson, S. (1996). Learning to do and learning to understand: A lesson and a challenge for cognitive modeling. In Reimann, P. & Spada, H. (Eds.), Learning in humans and machines (pp. 37–62). Pergamon, Elsevier Science.Google Scholar
Olson, G. M., & Olson, J. S. (2000). Distance matters. Human Computer Interaction, 15, 139–178. https://doi.org/10.1207/S15327051HCI1523_4CrossRefGoogle Scholar
O’Malley, C. (Ed.) (1995). Computer Supported Collaborative Learning. NATO ASI Series (Series F: Computer and Systems Sciences), vol. 128. Springer, Berlin. https://doi.org/10.1007/978-3-642-85098-1CrossRefGoogle Scholar
Palinscar, A. S., & Brown, A. L. (1986) Interactive teaching to promote independent learning from text. The Reading Teacher, 39, 771–777.Google Scholar
Panadero, E., & Järvelä, S. (2015). Socially shared regulation of learning: A review. European Psychologist, 20(3), 190–203. https://doi.org/10.1027/1016-9040/a000226CrossRefGoogle Scholar
Panhwar, A. H., Gopang, A. S., Chachar, Z. A. & Baloch, S. (2017). Differentiating cooperative learning and collaborative Learning: What is fit for Pakistani higher education? International Journal of English Linguistics, 7(5), 119–126. https://doi.org/10.5539/ijel.v7n5p119CrossRefGoogle Scholar
Panitz, T. (1996a). Collaborative versus cooperative Learning: A comparison of the two concepts which will help us understand the underlying nature of interactive Learning. Available at: https://eric.ed.gov/?id=ED448443Google Scholar
Panitz, T. (1996b). A definition of collaborative vs. cooperative learning. Available at: http://colccti.colfinder.org/sites/default/files/a_definition_of_collaborative_vs_cooperative_learning.pdf.Google Scholar
Panitz, T. (1999). Benefits of cooperative learning in relation to student motivation. In Theall, M. (Ed.), Motivation from within: Approaches for encouraging faculty and students to excel (New Directions for Teaching and Learning, pp. 59–68). Josey-Bass Publishing.Google Scholar
Panitz, T (2019). Cooperative learning (Chapter 3) [e-book version]. Available at: https://tpanitz.jimdo.com/ted-s-coop-learning-ebook/Google Scholar
Paul, R. C., Swart, W., Zhang, A. M., & MacLeod, K. R. (2015). Revisiting Zhang’s scale of transactional distance: Refinement and validation using structural equation modeling. Distance Education, 36(3), 364–382. https://doi.org/10.1080/01587919.2015.1081741CrossRefGoogle Scholar
Phielix, C., Prins, F. J., & Kirschner, P. A. (2010). Awareness of group performance in a CSCL-environment: Effects of peer feedback and reflection. Computers in Human Behavior, 26(2), 151–161. https://doi.org/10.1016/j.chb.2009.10.011CrossRefGoogle Scholar
Phirangee, K. & Malec, A. (2017) Othering in online learning: An examination of social presence, identity, and sense of community. Distance Education, 38(2), 160–172. https://doi.org/10.1080/01587919.2017.1322457CrossRefGoogle Scholar
Pigliapoco, E., & Bogliolo, A. (2008). The effects of psychological sense of community in online and face-to-face academic courses. International Journal of Emerging Technologies in Learning, 3(4), 60–69. http://dx.doi.org/10.3991/ijet.v3i4.201CrossRefGoogle Scholar
Popov, V., van Leeuwen, A., & Buis, S. C. A. (2017). Are you with me or not? Temporal synchronicity and transactivity during CSCL. Journal of Computer Assisted Learning, 33(5), 424–442. https://doi.org/10.1111/jcal.12185CrossRefGoogle Scholar
Pritchard, A., & Woollard, J. (2010). Psychology for the classroom: Constructivism and social learning. Routledge.Google Scholar
Puzio, K., & Colby, G. T. (2013). Cooperative learning and literacy: A meta-analytic review. .Journal of Research on Educational Effectiveness, 6(4), 339–360. https://doi.org/10.1080/19345747%20.2013.775683CrossRefGoogle Scholar
Raidal, S. L., & Volet, S. E. (2009). Preclinical students’ predispositions towards social forms of instruction and self-directed learning: A challenge for the development of autonomous and collaborative learners. Journal of Higher Education, 57, 577–596. https://doi.org/10.1007/s10734‑008-9163-zCrossRefGoogle Scholar
Raviv, A., Cohen, S., & Aflalo, E. (2019). How students learn in the school science laboratory? The benefits of cooperative learning. Research in Science Education, 49(2), 331–345. https://doi.org/10.1007/s11165-017-9618-2CrossRefGoogle Scholar
Resta, P., & Laferrière, T. (2007). Technology in support of collaborative learning. Educational Psychology Review, 19(1), 65–83. https://doi.org/10.1007/s10648-007-9042-7CrossRefGoogle Scholar
Robb, C. A., & Sutton, J. (2014). The importance of social presence and motivation in distance learning. The Journal of Technology, Management, and Applied Engineering, 30(2). Available at: https://cdn.ymaws.com/www.atmae.org/resource/resmgr/articles/robb___sutton-the_importance.pdfGoogle Scholar
Rochelle, J., & Teasley, S. D. (1995). The construction of shared knowledge in collaborative problem solving. In Malley, C. O (Ed.), Computer Supported Collaborative Learning. NATO ASI Series (Series F: Computer and Systems Sciences), vol. 128. Springer, Berlin. https://doi.org/10.1007/978-3-642-85098-1_5Google Scholar
Rockwood, R. (1995). Cooperative and collaborative learning. National Teaching and Learning Forum, 4(6). https://doi.org/10.1002/ntlf.10024Google Scholar
Rodríguez‐Triana, M. J., Martínez‐Monés, A., Asensio‐Pérez, J. I., & Dimitriadis, Y. (2015). Scripting and monitoring meet each other: Aligning learning analytics and learning design to support teachers in orchestrating CSCL situations. British Journal of Educational Technology, 46(2), 330–343. https://doi.org/10.1111/bjet.12198CrossRefGoogle Scholar
Roelofs, E., van der Linden, J., & Erkens, G. (2000). Leren in dialoog: Een discussie over samenwerkend leren in onderwijs en opleiding. In van der Linden, J. & Roelofs, E. (Eds.), Leren in dialoog: Een discussie over samenwerkend leren in onderwijs en opleiding (pp. 7– 34). Wolters-Noordhoff.Google Scholar
Rourke, L. (2000). Operationalizing social interaction in computer conferencing. In Proceedings of the 16th annual conference of the Canadian Association for Distance Education (pp. 335–353). Quebec City.Google Scholar
Rourke, L., & Anderson, T. (2002) Exploring social communication in asynchronous, text-based computer conferencing. Journal of Interactive Learning Research, 13(3), 259–275.Google Scholar
Sawyer, J., & Obeid, R. (2017). Cooperative and collaborative learning: Getting the best of both words. In Obeid, R., Schwartz, A., Shane-Simpson, C., & Brooks, P. J. (Eds.), How we teach now: The GSTA guide to student-centered teaching (pp. 163–177). Society for the Teaching of Psychology.Google Scholar
Scardamalia, M. (2002). Collective cognitive responsibility for the advancement of knowledge. In Smith, B. (Ed.), Liberal education in a knowledge society (pp. 67–98). Open Court.Google Scholar
Scardamalia, M., & Bereiter, C. (2003). Knowledge building. In Guthrie, J. W. (Ed.), Encyclopedia of education (pp. 1370–1373). Mcamillan Reference.Google Scholar
Schellens, T., Van Keer, H., De Wever, B., & Valcke, M. (2006). About scripting: The effects of two CSCL scripts on university students’ critical thinking. In Current developments in technology-assisted education: proceedings of m-ICTE2006 (vol. 2: Technological Science Education, Collaborative Learning, Knowledge Management, pp. 1374–1378). FORMATEX.Google Scholar
Shimazou, J., & Aldrich, H. (2010). Group work can be gratifying: Understanding and overcoming resistance to cooperative learning. College Teaching, 58(2),52–57. https://doi.org/10.1080/87567550903418594CrossRefGoogle Scholar
Shin, N. (2003). Transactional presence as a critical predictor of success in distance learning. Distance Education, 24, 69–86. https://doi.org/10.1080/01587910303048CrossRefGoogle Scholar
Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. Wiley.Google Scholar
Slavin, R. E. (1980). Cooperative learning. Review of Educational Research, 50(2), 315–345. https://doi.org/10.3102/00346543050002315CrossRefGoogle Scholar
Slavin, R. E. (1994). Student teams achievement divisions. In Sharan, S. (Ed.), Handbook of co-operative learning methods (pp. 3–19). Greenwood Press.Google Scholar
Slavin, R. E. (1997). Educational psychology: Theory and practice (5th ed.). Allyn & Bacon.Google Scholar
Slavin, R. E., & Cooper, R. (1999). Improving intergroup relations: Lessons learned from cooperative learning programs. Journal of Social Issues, 55(4), 647–663. https://doi.org/10.1111/0022-4537.00140CrossRefGoogle Scholar
Slof, B., Erkens, G., Kirschner, P. A., Jaspers, J., Janssen, J. & Phielix, C. (2010). Fostering complex learning-task performance through scripting student use of computer supported representational tools. Computers & Education, 55, 1707–1720. https://doi.org/10.1016/j.compedu.2010.07.016CrossRefGoogle Scholar
Soller, A. (2001). Supporting social interaction in an intelligent collaborative learning system. International Journal of Artificial Intelligence in Education, 12, 40–62.Google Scholar
Soller, A. L., Lesgold, A., Linton, F., & Goodman, B. (1999). What makes peer interaction effective? Modeling effective communication in an intelligent CSCL. In Brennan, S. E., Giboin, A. & Traum, D. (Eds.), Psychological models of communication in collaborative systems: Papers from the AIII Fall Symposium (Technical Report FS-99–03, pp. 116–123). The AAAI Press.Google Scholar
Spoelstra, H. (2015). Collaborations in open learning environment. Unpublished dissertation. Heerlen, The Netherlands: Open Universiteit.Google Scholar
Stahl, G., Koschmann, T., & Suthers, D. (2014). Computer-supported collaborative learning: An historical perspective. In Sawyer, R. K. (Ed.), Cambridge handbook of the learning sciences (2nd ed., pp. 479–500). Cambridge University Press.CrossRefGoogle Scholar
Staublitz, T., Pfeiffer, T., Renz, J., Willems, C., & Meinel, C. (2015). Collaborative learning in a MOOC environment. In Proceedings of the 8th international conference of education, research and innovation (pp. 8237–8246). IATED Academy. https://doi.org/10.1145/3051457.3053975Google Scholar
Stern, A., Schultze, T., & Schulz-Hardt, S. (2017). How much group is necessary? Group-to-individual transfer in estimation tasks. Collabra: Psychology, 3(1), 16. https://doi.org/10.1525/collabra.95CrossRefGoogle Scholar
Strijbos, J-W. (2004). The effect of roles on computer-supported collaborative learning. Unpublished doctoral dissertation. Heerlen, The Netherlands: Open Universiteit.Google Scholar
Strijbos, J-W., & Weinberger, A. (2010). Emerging and scripted roles in computer-supported collaborative learning. Computers in Human Behavior, 26(4), 491–494. https://doi.org/10.1016/j.chb.2009.08.006CrossRefGoogle Scholar
Thai, M., Sheeran, N., & Cummings, D. J. (2019). We’re all in this together: The impact of Facebook groups on social connectedness and other outcomes in higher education. The Internet and Higher Education, 40, 44–49. https://doi.org/10.1016/j.iheduc.2018.10.001CrossRefGoogle Scholar
Thoms, B., & Eryilmaz, E. (2014). How media choice affects learner interactions in distance learning classes. Computers & Education, 75, 112–126. https://doi.org/10.1016/j.compedu.2014.02.002CrossRefGoogle Scholar
Trope, Y., & Liberman, N. (2010). Construal-level theory of psychological distance. Psychological Review, 117(2), 440–463. https://doi.org/10.1037/a0018963CrossRefGoogle ScholarPubMed
Trope, Y., Liberman, N., & Wakslak, C. (2007). Construal levels and psychological distance: Effects on representation, prediction, evaluation, and behavior. Journal of Consumer Psychology, 17(2), 83–95. https://doi.org/0.1016/S1057-7408(07)70013-XCrossRefGoogle ScholarPubMed
Tuckman, B. W. (1965). Developmental sequence in small groups, Psychological Bulletin, 63(6), 384–399.CrossRefGoogle ScholarPubMed
Tuckman, B. W., & Jensen, M. A. (1977). Stages of small group development revisited. Group and Organizational Studies, 2, 419–427.CrossRefGoogle Scholar
Van Leeuwen, A., Janssen, J., Erkens, G., & Brekelmans, M. (2014). Supporting teachers in guiding collaborating students: Effects of learning analytics in CSCL. Computers & Education, 79, 28–39. https://doi.org/10.1016/j.compedu.2014.07.007CrossRefGoogle Scholar
Veerman, A. L. (2000). Computer-supported collaborative learning through argumentation. Unpublished doctoral dissertation. Enschede, The Netherlands: Print Partners Ipskamp.Google Scholar
Veldman, M. A., & Kostons, D. (2019). Cooperative and collaborative learning: Considering four dimensions of learning in groups. Pedagogische Studiën, 96, 76–81.Google Scholar
Vogel, F., Wecker, C., Kollar, I., & Fisher, F. (2017). Socio-cognitive scaffolding with computer-supported collaboration scripts: a meta-analysis. Educational Psychology Review, 28, 477–511. https://doi.org/10.1007/s10648-016-9361-7CrossRefGoogle Scholar
Vygotsky, L. S. (1978). Mind and society: The development of higher mental processes. Harvard University Press.Google Scholar
Wagner, E. D. (1994). In support of a functional definition of interaction. American Journal of Distance Education, 8(2), 6–29.CrossRefGoogle Scholar
Wagner, E. D. (1997). Interactivity: From agents to outcomes. New Directions for Teaching and Learning, 71, 19–26.CrossRefGoogle Scholar
Wang, J., & Fang, Y. (2005). Benefits of cooperative learning un Weblog networks. Available at: https://eric.ed.gov/?id=ED490815Google Scholar
Wang, S. & Lin, S. S. J. (2007). The effects of group composition of self-efficacy and collective efficacy on computer-supported collaborative learning. Computers in Human Behavior, 23, 2256–2268.CrossRefGoogle Scholar
Watson, G, & Johnson, D. W. (1972). Social psychology: Issues and insights (2nd ed.). Lippincott.Google Scholar
Weidlich, J., & Bastiaens, T. J. (2017). Explaining social presence and the quality of online learning with the SIPS model. Computers in Human Behavior, 72, 479–487. https://doi.org/10.1016/j.chb.2017.03.016CrossRefGoogle Scholar
Weidlich, J., & Bastiaens, T. J. (2018). Technology matters – The impact of transactional distance on satisfaction in online distance learning. International Review of Research in Open and Distributed Learning, 19(3). https://doi.org/10.19173/irrodl.v19i3.3417CrossRefGoogle Scholar
Weidlich, J., & Bastiaens, T. J. (2019). Designing sociable online learning environments and enhancing social presence: An affordance enrichment approach. Computers & Education, 142, 103622. https://doi.org/10.1016/j.compedu.2019.103622CrossRefGoogle Scholar
Weinberger, A. (2003). Scripts for computer-supported collaborative learning: Effects of social and epistemic scripts on collaborative knowledge construction. Unpublished PhD dissertation. München, Germany: Ludwig-Maximilians-Universität.Google Scholar
Weinberger, A., Stegmann, K., & Fischer, F. (2005). Computer-supported collaborative learning in higher education: Scripts for argumentative knowledge construction in distributed groups. In Koschmann, T., Suthers, D., & Chan, T. W. (Eds.), Proceedings of the international conference on Computer supported collaborative learning: learning 2005: The next 10 years! (pp. 717–726). Lawrence Erlbaum Associates.Google Scholar
Wheelan, S. A. (2004). Group processes: A developmental perspective (Vol. 34). Allyn and Bacon.Google Scholar
Wheelan, S. A., & Lisk, A. R. (2000). Cohort group effectiveness and the educational achievement of adult undergraduate students. Small Group Research, 31(6), 724–738.CrossRefGoogle Scholar
Wilkinson, T. W., & Sherman, T. M. (1991). Telecommunications-based distance education: Who’s doing what? Educational Technology, 31(11), 54–59. https://doi.org/0.1111/j.1937-8327.1998.tb00096.xGoogle Scholar
Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated engagement in learning. In Hacker, D., Dunlosky, J., & Graesser, A. (Eds.), Metacognition in educational theory and practice (pp. 277–304). Lawrence Erlbaum.Google Scholar
Winne, P. H., & Hadwin, A. F. (2008). The weave of motivation and self-regulated learning. In Schunk, D. H. & Zimmerman, B. J. (Eds.), Motivation and self-regulated learning: Theory, research, and applications (pp. 297–314). Erlbaum.Google Scholar
Winne, P. H., & Hadwin, A. F. (2013). nStudy: Tracing and supporting self-regulated learning in the Internet. In Azevedo, R. & Aleven, V. (Eds.), International handbook of metacognition and learning technologies (vol. 26., pp. 293–308). Springer Science+Business Media. https://doi.org/10.1007/978-1-4419-5546-3_20CrossRefGoogle Scholar
Winne, P. H., Hadwin, A. F., & Perry, N. E. (2013). Metacognition and computer-supported collaborative learning. In Hmelo-Silver, C., O’Donnell, A., Chan, C., & Chinn, C. (Eds.), International handbook of collaborative learning (pp. 462–479). Taylor & Francis.Google Scholar
Wise, A. F., Cui, Y., Jin, W., & Vytasek, J. (2017). Mining for gold: Identifying content-related MOOC discussion threads across domains through linguistic modeling. The Internet and Higher Education, 32, 11–28. https://doi.org/10.1016/j.iheduc.2016.08.001CrossRefGoogle Scholar
Wise, A. F., & Schwarz, B. B. (2017). Visions of CSCL: Eight provocations for the future of the field. International Journal of Computer-Supported Collaborative Learning, 12(4), 423–467. https://doi.org/10.1007/s11412–017–9267–5CrossRefGoogle Scholar
Wolters, C. A., & Benzon, M. B. (2013) Assessing and predicting college students’ use of strategies for the self-regulation of motivation, The Journal of Experimental Education, 81(2), 199–221. https://doi.org/10.1080/00220973.2012.699901CrossRefGoogle Scholar
Wood, D. M. & Chen, K-C. (2010). Evaluation techniques for cooperative learning. International Journal of Management & Information Systems, 14(1), 1–6. https://doi.org/10.19030/ijmis.v14i1.815Google Scholar
Zafra-Gómez, J. L., Román-Martínez, I., & Gómez-Miranda, M. E. (2015). Measuring the impact of inquiry-based learning on outcomes and student satisfaction. Assessment & Evaluation in Higher Education, 40(8), 1050–1069. https://doi.org/10.1080/02602938.2014.963836CrossRefGoogle Scholar
Zambrano, R. J., Kirschner, F., & Kirschner, P. A. (2018). The effect of the prior collaborative experience op the effectiveness and efficiency of collaborative learning. In Kay, J. & Luckin, R. (Eds.), Proceedings of the 13th international conference of the learning sciences: Rethinking learning in the digital age: Making the learning sciences count (ICLS 2018) (Vol 1., pp. 112–119). ICLS.Google Scholar
Zenios, M. (2011). Epistemic activities and collaborative learning: Towards an analytical model for studying knowledge construction in networked learning settings. Journal of Computer Assisted Learning, 27(3), 259–268. https://doi.org/10.1111/j.1365-2729.2010.00394.xCrossRefGoogle Scholar
Zheng, L., Li, X., & Huang, R. (2017). The effect of socially shared regulation approach on learning performance in computer-supported collaborative learning. Educational Technology & Society, 20(4), 35–46. https://doi.org/10.1027/1016-9040/a000226Google Scholar
Zheng, W., & Wei, J. (2018). Linking ethnic composition and performance: Information integration between majority and minority members. Small Group Research, 49(3), 357–387. https://doi.org/10.1177/1046496417749727CrossRefGoogle Scholar
Zheng, J., Xing, W., & Zhu, G. (2019). Examining sequential patterns of self-and socially shared regulation of STEM learning in a CSCL environment. Computers & Education, 136, 34–48. https://doi.org/10.1016/j.compedu.2019.03.005CrossRefGoogle Scholar
References
Achim, A. M., Guitton, M., Jackson, P. L., Boutin, A., & Monetta, L. (2013) On what ground do we mentalize? Characteristics of current tasks and sources of information that contribute to mentalizing judgments. Psychological Assessment, 25(1) 117–126.CrossRefGoogle ScholarPubMed
Adery, L. H., Ichinose, M., Torregrossa, L. J., Wade, J., Nichols, H., Bekele, E., et al. (2018). The acceptability and feasibility of a novel virtual reality based social skills training game for schizophrenia: Preliminary findings. Psychiatry Research, 270, 496–502.CrossRefGoogle ScholarPubMed
Adolphs, R. (2009). The social brain: Neural basis of social knowledge. Annual Review of Psychology, 60, 693–716.CrossRefGoogle ScholarPubMed
Akhtar, S., Justice, L. V., Loveday, C., & Conway, M. A. (2017). Switching memory perspective. Consciousness and Cognition, 56(Supplement C), 50–57.CrossRefGoogle ScholarPubMed
Avram, M., Hennig-Fast, K., Bao, Y., Pöppel, E., Reiser, M., Blautzik, J., … & Gutyrchik, E. (2014). Neural correlates of moral judgments in first and third-person perspectives: Implications for neuroethics and beyond. BMC Neuroscience, 15, 39.CrossRefGoogle ScholarPubMed
Bailenson, J. N., Beall, A. C., Blascovich, J., Loomis, J., & Turk, M. (2005). Transformed social interaction, augmented gaze, and social influence in immersive virtual environments. Human Communication Research, 31, 511–537.CrossRefGoogle Scholar
Bailenson, J. N., Beall, A. C., Loomis, J., Blascovich, J., & Turk, M. (2004). Transformed social interaction: Decoupling representation from behavior and form in collaborative virtual environments. Presence: Teleoperators & Virtual Environments, 13(4), 428–441.CrossRefGoogle Scholar
Bailenson, J. N., & Blascovich, J. (2004). Avatars. In Encyclopedia of human–computer interaction. Berkshire Publishing Group.Google Scholar
Bailenson, J. N., & Yee, N. (2005). Digital chameleons: Automatic assimilation of nonverbal gestures in immersive virtual environments. Psychological Science, 16(10), 814–819.CrossRefGoogle ScholarPubMed
Banakou, D., Kishore, S., & Slater, M. (2018). Virtually being Einstein results in an improvement in cognitive task performance and a decrease in age bias. Frontiers in Psychology, 9(917).CrossRefGoogle Scholar
Barfield, W., Zeltzer, D., Sheridan, T., & Slater, M. (1995). Presence and performance within virtual environments. In Barfield, W. & Furness (Eds.), T. A., Virtual environments and advanced interface design (pp. 473–513). Oxford University Press.CrossRefGoogle Scholar
Barkley, R. A. (2012). Executive functions: What they are, how they work, and why they evolved. Guilford Press.Google Scholar
Bastug, E., Bennis, M., Medard, M., & Debbah, M. (2017). Toward interconnected virtual reality: Opportunities, challenges, and enablers. IEEE Communications Magazine, 55(6), 110–117.CrossRefGoogle Scholar
Beauchamp, M. H. (2017). Neuropsychology’s social landscape: Common ground with social neuroscience. Neuropsychology, 31(8), 981.CrossRefGoogle ScholarPubMed
Bente, G., & Krämer, N. (2011). Virtual gestures: Embodiment and nonverbal behavior in computer-mediated communication. In Kappas, A. & Krämer, N. (Eds.), Face-to-face communication over the Internet: Emotions in a web of culture, language, and technology (Studies in Emotion and Social Interaction, pp. 176–210). Cambridge University Press.CrossRefGoogle Scholar
Bente, G., Krämer, N. C., & Eschenburg, F. (2008). Is there anybody out there. Mediated interpersonal communication, 131–157. www.taylorfrancis.com/chapters/edit/10.4324/9780203926864-16/anybody-analyzing-effects-embodiment-nonverbal-behavior-avatar-mediated-communication-gary-bente-nicole-kr%C3%A4mer-felix-eschenburg.Google Scholar
Bertrand, P., Guegan, J., Robieux, L., McCall, C. A., & Zenasni, F. (2018). Learning empathy through virtual reality: Multiple strategies for training empathy-related abilities using body ownership illusions in embodied virtual reality. Frontiers in Robotics and AI, 5(26).CrossRefGoogle ScholarPubMed
Biocca, F. (1997). The cyborg’s dilemma: Embodiment in virtual environments. Proceedings of the Second International Conference on Cognitive Technology Humanizing the Information Age, Aizu-Wakamatsu City, Japan, 1997 (pp. 12–26). doi: 10.1109/CT.1997.617676.CrossRefGoogle Scholar
Biocca, F., Harms, C., & Burgoo, J. K. (2003). Towards a more robust theory and measure of social presence: Review and suggested criteria. Presence, Teleoperators & Virtual Environments, 12(5), 456–80.CrossRefGoogle Scholar
Biocca, F., & Levy, M. R. (2013). Communication in the age of virtual reality. Routledge.CrossRefGoogle Scholar
Blanchard, C., Burgess, S., Harville, Y., Lanier, J., Lasko, A., Oberman, M., & Teitel, M. (1992). Reality built for two: A virtual reality tool. ACM SZGGRAPH Computer Graphics, 24(2), 35–36.CrossRefGoogle Scholar
Bohil, C. J., Alicea, B., & Biocca, F. A. (2011). Virtual reality in neuroscience research and therapy. Nature Review Neuroscience, 12, 752–762.CrossRefGoogle ScholarPubMed
Burin, D., Kilteni, K., Rabuffetti, M., Slater, M., & Pia, L. (2019). Body ownership increases the interference between observed and executed movements. PLoS ONE, 14(1), e0209899.CrossRefGoogle ScholarPubMed
Burin, D., Liu, Y., Yamaya, N., & Kawashima, R. (2020). Virtual training leads to physical, cognitive and neural benefits in healthy adults. NeuroImage, 222, 117297.CrossRefGoogle ScholarPubMed
Cacioppo, J. T., Berntson, G. G., & Decety, J. (2010). Social neuroscience and its relationship to social psychology. Social Cognition, 28(6), 675–685. https://doi.org/10.1521/soco.2010.28.6.675.CrossRefGoogle ScholarPubMed
Canty, A. L., Neumann, D. L., Fleming, J., & Shum, D. H. (2017). Evaluation of a newly developed measure of theory of mind: The virtual assessment of mentalising ability. Neuropsycholigical Rehabilitation, 27(5), 834–870.CrossRefGoogle ScholarPubMed
Cesa, G. L., Manzoni, G. M., Bacchetta, M., Castelnuovo, G., Conti, S., Gaggioli, A., et al. (2013). Virtual reality for enhancing the cognitive behavioral treatment of obesity with binge eating disorder: Randomized controlled study with one-year follow-up. Journal of Medical Internet Research, 15(6), e113.CrossRefGoogle ScholarPubMed
Chisholm, J. D., Chapman, C. S., Amm, M., Bischof, W. F., Smilek, D., & Kingstone, A. (2014). A cognitive ethology study of first- and third-person perspectives. PLoS ONE, 9, e92696.CrossRefGoogle ScholarPubMed
Cipresso, P. (2015). Modeling behavior dynamics using computational psychometrics within virtual worlds. Frontiers in Psychology, 6(1725).CrossRefGoogle ScholarPubMed
Cipresso, P., Serino, S., & Riva, G. (2016). Psychometric assessment and behavioral experiments using a free virtual reality platform and computational science. BMC Medical Informatics and Decision Making, 16(1), 1–11.CrossRefGoogle ScholarPubMed
Collins, F. S., & Riley, W. T. (2016). NIH’s transformative opportunities for the behavioral and social sciences. Science Translational Medicine, 8(366), 366ed14.CrossRefGoogle ScholarPubMed
Craig, T. K. J., Rus-Calafell, M., Ward, T., Leff, J. P., Huckvale, M., Howarth, E., et al. (2018). AVATAR therapy for auditory verbal hallucinations in people with psychosis: A single-blind, randomised controlled trial. The Lancet Psychiatry, 5(1), 31–40.CrossRefGoogle ScholarPubMed
Cruz-Neira, C., Sandin, D. J., DeFanti, T. A., Kenyon, R. V., & Hart, J. C. (1992). The CAVE: Audio visual experience automatic virtual environment. Communications of the ACM, 35(6), 64–72. DOI: https://doi.org/10.1145/129888.129892.CrossRefGoogle Scholar
Cushman, F. (2013). Action, outcome, and value: A dual-system framework for morality. Personality and Social Psychology Review, 17(3), 273–292.CrossRefGoogle ScholarPubMed
de Borst, A. W., & de Gelder, B. (2015). Is it the real deal? Perception of virtual characters versus humans: An affective cognitive neuroscience perspective. Frontiers in Psychology, 6, 576.CrossRefGoogle ScholarPubMed
de Jaegher, H., di Paolo, E., & Gallagher, S. (2010). Can social interaction constitute social cognition? Trends in Cognitive Science, 14, 441–447.CrossRefGoogle ScholarPubMed
Didehbani, N., Allen, T., Kandalaft, M., Krawczyk, D., & Chapman, S. (2016). Virtual reality social cognition training for children with high functioning autism. Computers in Human Behavior, 62, 703–711.CrossRefGoogle Scholar
Dooley, J. J., Beauchamp, M., & Anderson, V. A. (2010). The measurement of sociomoral reasoning in adolescents with traumatic brain injury: A pilot investigation. Brain Impairment, 11(2), 152–161.CrossRefGoogle Scholar
Dyck, M., Winbeck, M., Leiberg, S., Chen, Y., Gur, R. C., & Mathiak, K. (2008). Recognition profile of emotions in natural and virtual faces. PLoS ONE, 3(11), e3628.CrossRefGoogle ScholarPubMed
Dzardanova, E., Kasapakis, V., & Gavalas, D. (2018) Social Virtual Reality. In Lee, N. (Ed.), Encyclopedia of computer graphics and games. Springer, Cham. https://doi.org/10.1007/978-3-319-08234-9_204-1.Google Scholar
Faas, D., Bao, Q., Frey, D., & Yang, M. (2014). The influence of immersion and presence in early stage engineering designing and building. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 28(2), 139–151. DOI: 10.1017/S0890060414000055CrossRefGoogle Scholar
Feijt, M. A., De Kort, Y. A., Westerink, J. W., & Ijsselsteijn, W. A. (2018). Enhancing empathic interactions in mental health care: Opportunities offered through social interaction technologies. Annual Review of Cybertherapy and Telemedicine, 16, 25–30.Google Scholar
Foot, P. (1967). The problem of abortion and the doctrine of double effect. Oxford Review, 5.Google Scholar
Fox, J., Ahn, S. J., Janssen, J. H., Yeykelis, L., Segovia, K. Y., & Bailenson, J. N. (2015) Avatars versus agents: A meta-analysis quantifying the effect of agency on social influence. Human–Computer Interaction, 30(5), 401–432.CrossRefGoogle Scholar
Francis, K. B., Howard, C., Howard, I. S., Gummerum, M., Ganis, G., Anderson, G., & Terbeck, S. (2016). Virtual morality: Transitioning from moral judgment to moral action? PLoS ONE, 11(10), e0164374.CrossRefGoogle ScholarPubMed
Francová, A., Darmová, B., Stopková, P., Kosová, J., & Fajnerová, I. (2019). Virtual Reality Exposure Therapy in Patients with Obsessive-Compulsive Disorder. Paper presented at the 2019 International Conference on Virtual Rehabilitation. ICVR, 21–24 July 2019.CrossRefGoogle Scholar
Freeman, D., Yu, L.-M., Kabir, T., Martin, J., Craven, M., Leal, J., et al. (2019). Automated virtual reality (VR) cognitive therapy for patients with psychosis: Study protocol for a single-blind parallel group randomised controlled trial (gameChange). BMJ Open, 9(8), e031606.CrossRefGoogle ScholarPubMed
Friston, K. (2018). Does predictive coding have a future? Nature Neuroscience, 21(8), 1019–1021.CrossRefGoogle ScholarPubMed
Gaggioli, A., Pallavicini, F., Morganti, L., Serino, S., Scaratti, C., Briguglio, M., et al. (2014). Experiential virtual scenarios with real-time monitoring (interreality) for the management of psychological stress: A block randomized controlled trial. Journal of Medical Internet Research, 16(7), e167.CrossRefGoogle ScholarPubMed
Genon, S., Reid, A., Langner, R., Amunts, K., & Eickhoff, S. B. (2018). How to characterize the function of a brain region. Trends in Cognitive Sciences, 22(4), 350–364.CrossRefGoogle ScholarPubMed
Ginzburg, K., Tsur, N., Barak-Nahum, A., & Defrin, R. (2014). Body awareness: Differentiating between sensitivity to and monitoring of bodily signals. Behavioural Medicine, 37(3), 564–575.CrossRefGoogle ScholarPubMed
Grassini, S., Laumann, K., & Rasmussen Skogstad, M. (2020). The use of virtual reality alone does not promote training performance (but sense of presence does). Frontiers in Psychology, 11, 1743. https://doi.org/10.3389/fpsyg.2020.01743CrossRefGoogle ScholarPubMed
Greene, J. D., Cushman, F. A., Stewart, L. E., Lowenberg, K., Nystrom, L. E., & Cohen, J. D. (2009) Pushing moral buttons: The interaction between personal force and intention in moral judgment. Cognition, 111(3), 364–371.CrossRefGoogle ScholarPubMed
Greene, J. D., Sommerville, R. B., Nystrom, L. E., Darley, J. M., & Cohen, J. D. (2001). An fMRI investigation of emotional engagement in moral judgment. Science, 293(5537), 2105–2108.CrossRefGoogle ScholarPubMed
Gregory, N. J., López, B., Graham, G., Marshman, P., Bate, S., Kargas, N. (2015). Reduced gaze following and attention to heads when viewing a “live” social scene. PLoS ONE. doi:10.1371/journal.pone.0121792CrossRefGoogle Scholar
Gutiérrez-Maldonado, J., Wiederhold, B. K., & Riva, G. (2016). Future directions: How virtual reality can further improve the assessment and treatment of eating disorders and obesity. Cyberpsychology, Behavior & Social Networking, 19(2), 148–153.CrossRefGoogle Scholar
Hale, J., & Antonia, F. D. C. (2016). Testing the relationship between mimicry, trust and rapport in virtual reality conversations. Scientific Reports, 6, 35295.CrossRefGoogle ScholarPubMed
Hauser, M., Young, L., & Cushman, F. (2008). Reviving Rawls’ linguistic analogy: Operative principles and the causal structure of moral actions. In Sinnott-Armstrong, W. (Ed.), Moral psychology and biology. Oxford University Press.Google Scholar
Hogenelst, K., Schoevers, R. A., & aan het Rot, M. (2015). Studying the neurobiology of human social interaction: Making the case for ecological validity. Social Neuroscience, 2015(10), 219–229.CrossRefGoogle Scholar
Hove, M. J., & Risen, J. L. (2009). It’s all in the timing: Interpersonal synchrony increases affiliation. Social Cognition, 27(6), 949–960.CrossRefGoogle Scholar
Jerald, J. (2015). The VR book: Human-centered design for virtual reality. Association for Computing Machinery and Morgan & Claypool.CrossRefGoogle Scholar
Jolly, E., & Chang, L. (2019). The flatland fallacy: Moving beyond low-dimensional thinking. Topics in Cognitive Science, 11(2), 433–454.CrossRefGoogle ScholarPubMed
Jonas, M., Said, S., Yu, D., Aiello, C., Furlo, N., & Zytko, D. (2019). Towards a taxonomy of Social VR application design. In Extended Abstracts of the Annual Symposium on Computer–Human Interaction in Play Companion Extended Abstracts (CHI PLAY ’19 Extended Abstracts). Association for Computing Machinery, 437–444. https://doi.org/10.1145/3341215.3356271CrossRefGoogle Scholar
Keizer, A., van Elburg, A., Helms, R., & Dijkerman, H. C. (2016). A virtual reality full body illusion improves body image disturbance in anorexia nervosa. PLoS ONE, 11(10), e0163921.CrossRefGoogle ScholarPubMed
Kennedy, D. P., & Adolphs, R. (2012). The social brain in psychiatric and neurological disorders. Trends in Cognitive Sciences, 16, 559–572.CrossRefGoogle ScholarPubMed
Kenny, P., & Parsons, T. D. (2011; Co-lead authors) Embodied conversational virtual human patients. In Perez-Marin, C. & Pascual-Nieto, I. (Eds.), Conversational Agents and Natural Language Interaction: Techniques and Effective Practices (pp. 254– 281). IGI Global.CrossRefGoogle Scholar
Klin, A. (2000) Attributing social meaning to ambiguous visual stimuli in higher-functioning autism and Asperger syndrome: The social attribution task. The Journal of Child Psychology and Psychiatry and Allied Disciplines, 41(7), 831–846.CrossRefGoogle ScholarPubMed
Kruzan, K. P., & Won, A. S. (2019). Embodied well-being through two media technologies: Virtual reality and social media. New Media & Society, 21(8), 1734–1749.CrossRefGoogle Scholar
Laforest, M., Bouchard, S., Crétu, A.-M., & Mesly, O. (2016). Inducing an anxiety response using a contaminated virtual environment: Validation of a therapeutic tool for obsessive–compulsive disorder. Frontiers in ICT, 3(18).CrossRefGoogle Scholar
Launay, J., Dean, R. T., & Bailes, F. (2013). Synchronization can influence trust following virtual interaction. Experimental Psychology, 60(1), 53–63.CrossRefGoogle ScholarPubMed
Launay, J., Dean, R. T., & Bailes, F. (2014). Synchronising movements with the sounds of a virtual partner enhances partner likeability. Cognitive Processing, 15(4), 491–501.CrossRefGoogle ScholarPubMed
Lee, K. M. (2004). Presence, explicated. Communication Theory, 14(1), 27–50. https://doi.org/10.1111/j.1468-2885.2004.tb00302.x.CrossRefGoogle Scholar
Lindner, P., Hamilton, W., Miloff, A., & Carlbring, P. (2019). How to treat depression with low-intensity virtual reality interventions: Perspectives on translating cognitive behavioral techniques into the virtual reality modality and how to make anti-depressive use of virtual reality–unique experiences. Frontiers in Psychiatry, 10(792), 1–6.CrossRefGoogle ScholarPubMed
Manzoni, G. M., Cesa, G. L., Bacchetta, M., Castelnuovo, G., Conti, S., Gaggioli, A., et al. (2016). Virtual reality-enhanced cognitive-behavioral therapy for morbid obesity: A randomized controlled study with 1 year follow-up. Cyberpsychology, Behavior & Social Networking, 19(2), 134–140.CrossRefGoogle ScholarPubMed
McDonnell, R., Jorg, S., McHugh, J., Newell, F., O’Cullivan, C. (2008). Evaluating the emotional content of human motions on real and virtual characters. In Proceedings of the 5th Symposium on Applied Perception in Graphics and Visualization APGV, Los Angeles, CA, USA, 9–10 August 2008. ACM Press.Google Scholar
Meister, L., Slater, M., Sanchez-Vives, M. V., Tsakiris, M. (2015) Changing bodies changes minds: Owning another body affects social cognition. Trends in Cognitive Sciences, 19(1) 6–12.CrossRefGoogle Scholar
Mesa-Gresa, P., Gil-Gomez, H., Lozano-Quilis, J. A., & Gil-Gomez, J. A. (2018). Effectiveness of virtual reality for children and adolescents with autism spectrum disorder: An evidence-based systematic review. Sensors (Basel), 18(8).CrossRefGoogle ScholarPubMed
Morasse, F., Vera Estay, E., & Beauchamp, M. H. (2020). Using virtual reality to optimize assessment of sociomoral skills. Virtual Reality, https://doi.org/10.1007/s10055-020-00443-9CrossRefGoogle Scholar
Moser, E., Derntl, B., Robinson, S., Fink, B., Gur, R. C., & Grammer, K. (2007). Amygdala activation at 3T in response to human and avatar facial expressions of emotions. Journal of Neuroscience Methods, 161(1), 126–133.CrossRefGoogle ScholarPubMed
Nash, E. B., Edwards, G. W., Thompson, J. A., & Barfield, W. (2000). A review of presence and performance in virtual environments. International Journal of Human–Computer Interaction, 12(1), 1–41.CrossRefGoogle Scholar
Navarrete, C. D., McDonald, M. M., Mott, M. L., & Asher, B. (2012). Virtual morality: Emotion and action in a simulated three-dimensional “trolley problem”. Emotion, 12(2), 364.CrossRefGoogle Scholar
Normand, J. M., Giannopoulos, E., Spanlang, B., & Slater, M. (2011). Multisensory stimulation can induce an illusion of larger belly size in immersive virtual reality. PLoS ONE, 6(1), 1–10.CrossRefGoogle ScholarPubMed
Oh, C. S., Bailenson, J. N., & Welch, G. F. (2018) A systematic review of social presence: Definition, antecedents, and implications. Frontiers in Robotics and AI, 5( 114). doi: 10.3389/frobt.2018.00114Google ScholarPubMed
Osimo, S. A., Pizarro, R., Spanlang, B., & Slater, M. (2015). Conversations between self and self as Sigmund Freud – A virtual body ownership paradigm for self counselling. Scientific Reports, 5.CrossRefGoogle Scholar
Pan, X., & Hamilton, A. (2018). Why and how to use virtual reality to study human social interaction: The challenges of exploring a new research landscape. British Journal of Psychology, 109(3), 395–417. https://doi.org/10.1111/bjop.12290CrossRefGoogle ScholarPubMed
Pan, X., & Slater, M. (2011). Confronting a moral dilemma in virtual reality: A pilot study. In Proceedings of the 25th BCS Conference on Human–Computer Interaction (BCS-HCI ’11). BCS Learning & Development Ltd., 46–51.Google Scholar
Parsons, T., Gaggioli, A., & Riva, G. (2017). Virtual reality for research in social neuroscience. Brain Sciences, 7(4), 42.CrossRefGoogle ScholarPubMed
Parsons, T. D. (2011). Affect-sensitive virtual standardized patient interface system. In Surry, D., Stefurak, T., & Gray, R. (Eds.), Technology integration in higher education: Social and organizational aspects (pp. 201–221). IGI Global.CrossRefGoogle Scholar
Parsons, T. D. (2015). Virtual reality for enhanced ecological validity and experimental control in the clinical, affective and social neurosciences. Frontiers in Human Neuroscience, 9, 660.CrossRefGoogle ScholarPubMed
Parsons, T. D. (2017). Cyberpsychology and the brain: The interaction of neuroscience and affective computing. Cambridge University Press.CrossRefGoogle Scholar
Parsons, T. D. (2019). Ethical challenges in digital psychology and cyberpsychology. Cambridge University Press.CrossRefGoogle Scholar
Parsons, T. D., & Duffield, T. (2019). National Institutes of Health initiatives for advancing scientific developments in clinical neuropsychology. The Clinical Neuropsychologist, 33, 246–270.CrossRefGoogle ScholarPubMed
Patil, I., Cogoni, C., Zangrando, N., Chittaro, L., & Silani, G. (2014). Affective basis of judgment–behavior discrepancy in virtual experiences of moral dilemmas. Social Neuroscience, 9(1), 94–107.CrossRefGoogle ScholarPubMed
Pavone, E. F., Tieri, G., Rizza, G., Tidoni, E., Grisoni, L., & Aglioti, S. M. (2016). Embodying others in immersive virtual reality: Electro-cortical signatures of monitoring the errors in the actions of an avatar seen from a first-person perspective. The Journal of Neuroscience, 36, 268–279.CrossRefGoogle ScholarPubMed
Peck, T. C., Seinfeld, S., Aglioti, S. M., Slater, M. (2013). Putting yourself in the skin of a black avatar reduces implicit racial bias. Conscious and Cognition, 22(3), 779–787.CrossRefGoogle Scholar
Petkova, V. I., & Ehrsson, H. H. (2008). If I were you: Perceptual illusion of body swapping. PLoS ONE, 3(12), e3832.CrossRefGoogle Scholar
Petkova, V. I., Khoshnevis, M., & Ehrsson, H. H. (2011). The perspective matters! Multisensory integration in ego-centric reference frames determines full-body ownership. Frontiers in Psychology, 2, 35.CrossRefGoogle ScholarPubMed
Porras-Garcia, B., Serrano-Troncoso, E., Carulla-Roig, M., Soto-Usera, P., Ferrer-Garcia, M., Figueras-Puigderrajols, N., et al. (2020). Virtual reality body exposure therapy for anorexia nervosa. A case report with follow-up results. Frontiers in Psychology, 11(956), 1–9.CrossRefGoogle ScholarPubMed
Preston, C., & Ehrsson, H. H. (2014). Illusory changes in body size modulate body satisfaction in a way that is related to non-clinical eating disorder psychopathology. PLoS ONE, 9(1), 1–9.CrossRefGoogle Scholar
Preston, C., & Ehrsson, H. H. (2016). Illusory obesity triggers body dissatisfaction responses in the insula and anterior cingulate cortex. Cerebral Cortex, 26(12), 4450–4460.CrossRefGoogle ScholarPubMed
Price, C. J. (2018). The evolution of cognitive models: From neuropsychology to neuroimaging and back. Cortex, 107, 37–49.CrossRefGoogle ScholarPubMed
Reader, A. T., & Holmes, N. P. (2016). Examining ecological validity in social interaction: Problems of visual fidelity, gaze, and social potential. Culture and Brain, 4, 134–46.CrossRefGoogle ScholarPubMed
Repetto, C., Gorini, A., Algeri, D., Vigna, C., Gaggioli, A., & Riva, G. (2009). The use of biofeedback in clinical virtual reality: The Intrepid project. Studies in Health, Technology and Informatics, 144, 128–132.Google ScholarPubMed
Risko, E. F., Laidlaw, K. E., Freeth, M., Foulsham, T., & Kingstone, A. (2012). Social attention with real versus reel stimuli: Toward an empirical approach to concerns about ecological validity. Frontiers in Human Neuroscience, 6, 143.CrossRefGoogle ScholarPubMed
Riva, G. (2008). From virtual to real body: Virtual reality as embodied technology. Journal of Cybertherapy and Rehabilitation, 1(1), 7–22.Google Scholar
Riva, G. (2011). The key to unlocking the virtual body: Virtual reality in the treatment of obesity and eating disorders. Journal of Diabetes Science and Technology, 5(2), 283–292.CrossRefGoogle ScholarPubMed
Riva, G. (2016). Embodied medicine: What human–computer confluence can offer to health care. In Gaggioli, A., Ferscha, A., Riva, G., Dunne, S., & Viaud-Delmon, I. (Eds.), Human–computer confluence: Transforming human experience through symbiotic technologies (pp. 55–79). De Gruyter Open.Google Scholar
Riva, G., Baños, R. M., Botella, C., Mantovani, F., & Gaggioli, A. (2016). Transforming experience: The potential of augmented reality and virtual reality for enhancing personal and clinical change. Frontiers in Psychiatry, 7(164), 1–14.CrossRefGoogle ScholarPubMed
Riva, G., & Dakanalis, A. (2018). Altered processing and integration of multisensory bodily representations and signals in eating disorders: A possible path toward the understanding of their underlying causes. Frontiers in Human Neuroscience, 12(49), 1–7.CrossRefGoogle ScholarPubMed
Riva, G., & Gaudio, S. (2018). Locked to a wrong body: Eating disorders as the outcome of a primary disturbance in multisensory body integration. Consciousness and Cognition, 59, 57–59.CrossRefGoogle Scholar
Riva, G., & Mantovani, F. (2014). Extending the self through the tools and the others: A general framework for presence and social presence in mediated interactions. In Interacting with presence: HCI and the sense of presence in computer-mediated environments (pp. 9–31). De Gruyter.Google Scholar
Riva, G., Serino, S., Di Lernia, D., Pavone, E. F., & Dakanalis, A. (2017). Embodied medicine: Mens sana in corpore virtuale sano. Frontiers in Human Neuroscience, 11(120).CrossRefGoogle ScholarPubMed
Riva, G., Waterworth, J. A., Waterworth, E. L., & Mantovani, F. (2011). From intention to action: The role of presence. New Ideas in Psychology, 29, 24–37.CrossRefGoogle Scholar
Riva, G., Wiederhold, B. K., & Mantovani, F. (2019). Neuroscience of virtual reality: From virtual exposure to embodied medicine. Cyberpsychology, Behavior and Social Networking, 22(1), 82–96.CrossRefGoogle ScholarPubMed
Roth, D., Latoschik, M., Vogeley, K., & Bente, G. (2015). Hybrid avatar-agent technology – A conceptual step towards mediated “social” virtual reality and its respective challenges. i-com, 14(2), 107–114. doi: https://doi.org/10.1515/icom-2015-0030.CrossRefGoogle Scholar
Russo-Ponsaran, N., McKown, C., Johnson, J., Russo, J., Crossman, J., & Reife, I. (2018). Virtual environment for social information processing: Assessment of children with and without autism spectrum disorders. Autism Research, 11(2), 305–317.CrossRefGoogle ScholarPubMed
Sadowski, W., & Stanney, K. (2002). Presence in virtual environments. In Stanney, K. M. (Ed.), Human factors and ergonomics. Handbook of virtual environments: Design, implementation, and applications (pp. 791–806). Lawrence Erlbaum Associates Publishers.Google Scholar
Salminen, M., Järvelä, S., Ruonala, A., et al. (2018). Bio-adaptive Social VR to evoke affective interdependence (pp. 73–77). Association for Computing Machinery.Google Scholar
Salminen, M., Järvelä, S., Ruonala, A., Harjunen, V., Jacucci, G., Hamari, J., et al. (2019). Evoking physiological synchrony and empathy using social VR with biofeedback. IEEE Transactions on Affective Computing.Google Scholar
Schoeller, F., Bertrand, P., Gerry, L. J., Jain, A., Horowitz, A. H., & Zenasni, F. (2019). Combining virtual reality and biofeedback to foster empathic abilities in humans. Frontiers in Psychology, 9(2741), 1–5.CrossRefGoogle ScholarPubMed
Schultheis, M. T., & Rizzo, A. A. (2001). The application of virtual reality technology in rehabilitation. Rehabilitation Psychology, 46(3), 296–311.CrossRefGoogle Scholar
Schwartz, R., & Steptoe, W. (2018). The immersive VR self: Performance, embodiment and presence in immersive virtual reality environments. In Papacharissi, Z. (Ed.), A networked self and human augmentics, artificial intelligence, sentience. Routledge. https://doi.org/10.4324/9781315202082Google Scholar
Serino, S., Baglio, F., Rossetto, F., Realdon, O., Cipresso, P., Parsons, T. D., et al. (2017). Picture Interpretation Test (PIT) 360 degrees: An innovative measure of executive functions. Scientific Reports, 7.CrossRefGoogle Scholar
Serino, S., & Dakanalis, A. (2017). Bodily illusions and weight-related disorders: Clinical insights from experimental research. Annals of Physical Rehabilitation Medicine, 60(3), 217–219.CrossRefGoogle ScholarPubMed
Serino, S., Pedroli, E., Keizer, A., Triberti, S., Dakanalis, A., Pallavicini, F., et al. (2016). Virtual reality body swapping: A tool for modifying the allocentric memory of the body. Cyberpsycholy, Behavior and Social Networking, 19(2), 127–133.CrossRefGoogle ScholarPubMed
Serino, S., Polli, N., & Riva, G. (2019). From avatars to body swapping: The use of virtual reality for assessing and treating body-size distortion in individuals with anorexia. Journal of Clinical Psychology, 75(2), 313–322.CrossRefGoogle ScholarPubMed
Serino, S., Scarpina, F., Chirico, A., Dakanalis, A., Di Lernia, D., Colombo, D., Catallo, V., Pedroli, E., & Riva, G. (in press). Gulliver’s virtual travels: Active embodiment in extreme body sizes for modulating our body representations. Cognitive Processing. https://link.springer.com/article/10.1007/s10339-020-00977-5Google Scholar
Serino, S., Scarpina, F., Keizer, A., Pedroli, E., Dakanalis, A., Castelnuovo, G., et al. (2016). A novel technique for improving bodily experience in a non-operable super-super obesity case. Frontiers in Psychology, 7(837). doi: 10.3389/fpsyg.2016.00837.CrossRefGoogle Scholar
Short, J. A., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. Wiley.Google Scholar
Skulmowski, A., Bunge, A., Kaspar, K., & Pipa, G. (2014). Forced-choice decision-making in modified trolley dilemma situations: A virtual reality and eye tracking study. Frontiers in Behavioral Neuroscience, 8, 426.CrossRefGoogle ScholarPubMed
Slater, M., Spanlang, B., Sanchez-Vives, M. V., & Blanke, O. (2010). First person experience of body transfer in virtual reality. PLoS ONE, 5, e10564.CrossRefGoogle ScholarPubMed
Slater, M., & Wilbur, S. (1997). A framework for immersive virtual environments (FIVE): Speculations on the role of presence in virtual environments. Presence, Teleoperators and Virtual Environments, 6, 603–616. doi: 10.1162/pres.1997.6.6.603CrossRefGoogle Scholar
Steptoe, W., & Steed, A. (2012). Multimodal data capture and analysis of interaction in immersive collaborative virtual environments. Presence, 21(4), 388–405.CrossRefGoogle Scholar
Suzuki, K., Garfinkel, S. N., Critchley, H. D., & Seth, A. K. (2013). Multisensory integration across exteroceptive and interoceptive domains modulates self-experience in the rubber-hand illusion. Neuropsychologia, 51(13), 2909–2917.CrossRefGoogle ScholarPubMed
Talsma, D. (2015). Predictive coding and multisensory integration: An attentional account of the multisensory mind. Frontiers in Integrative Neuroscience, 9, 19.CrossRefGoogle ScholarPubMed
Tarr, B., Slater, M., & Cohen, E. (2018). Synchrony and social connection in immersive Virtual Reality. Scientific Reports, 8(1), 1–8.CrossRefGoogle ScholarPubMed
Triberti, S., Durosini, I., Aschieri, F., Villani, D., & Riva, G. ( 2017 ). Changing avatars, changing selves? The influence of social and contextual expectations on digital rendition of identity. Cyberpsycholy, Behavior and Social Networking, 20(8), 501–507. doi:10.1089/cyber.2016.0424.CrossRefGoogle ScholarPubMed
Valdesolo, P., & DeSteno, D. (2011). Synchrony and the social tuning of compassion. Emotion, 11(2), 262.CrossRefGoogle ScholarPubMed
Van Vugt, E., Gibbs, J., Stams, G. J., Bijleveld, C., Hendriks, J., & van der Laan, P. (2011). Moral development and recidivism: A meta-analysis. International Journal of Offender Therapy and Comparative Criminology, 55(8), 1234–1250.CrossRefGoogle ScholarPubMed
Verhulst, A., Normand, J.-M., Lombart, C., Sugimoto, M., & Moreau, G. (2018). Influence of being embodied in an obese virtual body on shopping behavior and products perception in VR. Frontiers in Robotics and AI, 5, 1–20.CrossRefGoogle Scholar
Vogeley, K., May, M., Ritzl, A., Falkai, P., Zilles, K., & Fink, G. R. (2004). Neural correlates of first-person perspective as one constituent of human self-consciousness. Journal of Cognitive Neuroscience, 16(5), 817–827.CrossRefGoogle ScholarPubMed
Ward, J., & Meijer, P. (2010). Visual experiences in the blind induced by an auditory sensory substitution device. Consciousness and Cognition, 19(1), 492–500.CrossRefGoogle Scholar
Waterworth, J. A., & Waterworth, E. L. (2014). Altered, expanded and distributed embodiment: The three stages of interactive presence. In Riva, G., Waterworth, J. A., & Murray, D. (Eds.), Interacting with presence: HCI and the sense of presence in computer-mediated environments (pp. 36–50). De Gruyter Open – Online. www.presence-research.comGoogle Scholar
Wiltermuth, S. S., & Heath, C. (2009). Synchrony and cooperation. Psychological Science, 20(1), 1–5.CrossRefGoogle ScholarPubMed
Winter, K., Spengler, S., Bermpohl, F., Singer, T., & Kanske, P. (2017) Social cognition in aggressive offenders: Impaired empathy, but intact theory of mind. Scientific Reports, 7(1), 670–680.CrossRefGoogle ScholarPubMed
Yaremych, H. E., & Persky, S. (2019). Tracing physical behavior in virtual reality: A narrative review of applications to social psychology. Journal of Experimental Social Psychology, 85, 103845.CrossRefGoogle ScholarPubMed
Yee, N., & Bailenson, J. (2007). The Proteus Effect: The effect of transformed self-representation on behavior. Human Communication Research, 33(3), 271–290.CrossRefGoogle Scholar
Yee, N., Bailenson, J. N., & Ducheneaut, N. (2009). The Proteus Effect: Implications of transformed digital self-representation on online and offline behavior. Communication Research, 36(2), 285–312.CrossRefGoogle Scholar
Yuan, Y., Steed, A. (2010). Is the rubber hand illusion induced by immersive virtual reality? 2010 IEEE Virtual Reality Conference (VR) (pp. 95–102). doi: 10.1109/VR.2010.5444807.CrossRefGoogle Scholar
Zaki, J., & Ochsner, K. (2009). The need for a cognitive neuroscience of naturalistic social cognition. Annals of the New York Academy of Sciences, 1167(16).CrossRefGoogle ScholarPubMed
References
Allen, D. G., Mahto, R. V., & Otondo, R. F. (2007). Web-based recruitment: Effects of information, organizational brand, and attitudes toward a Web site on applicant attraction. Journal of Applied Psychology, 92(6), 16–96.CrossRefGoogle Scholar
Altimeter. (2011). Social business readiness: How advanced companies prepare internally. www.slideshare.net/jeremiah_owyang/social-readiness-how-advancedcompanies-prepareGoogle Scholar
Auxier, B. (2020). Most Americans support right to have some personal info removed from online searches. Pew Research Center. www.pewresearch.org/fact-tank/2020/01/27/most-americans-support-right-to-have-some-personal-info-removed-from-online-searches/Google Scholar
Avery, C., & Zabel, D. (2001). The flexible workplace: A sourcebook of information and research. Quorum Books.Google Scholar
Azucar, D., Marengo, D., & Settanni, M. (2018). Predicting the Big 5 personality traits from digital footprints on social media: A meta-analysis. Personality and Individual Differences, 124, 150–159.CrossRefGoogle Scholar
Back, M. D., Stopfer, J. M., Vazire, S., Gaddis, S., Schmukle, S. C., Egloff, B., & Gosling, S. D. (2010). Facebook profiles reflect actual personality, not self-idealization. Psychological Science, 21(3), 372–374.CrossRefGoogle Scholar
Barnes, N. G., Mazzola, A., & Killeen, M. (2019). Oversaturation & Disengagement: The 2019 Fortune 500 Social Media Dance. University of Massachusetts Dartmouth Research Center. www.umassd.edu/cmr/research/2019-fortune-500.htmlGoogle Scholar
Bell, J. D. (2018, September). Firing for online behavior. SHRM HR Today Magazine. www.shrm.org/hr-today/news/hr-magazine/0918/pages/firing-for-online-behavior-.aspxGoogle Scholar
Berger, J. L., & Zickar, M. J. (2016). Theoretical propositions about cybervetting: A common antecedents model. In Landers, R. N. & Schmidt, G. B. (Eds.), Social media in employee selection and recruitment: Theory, practice, and current challenges (pp. 43–58). Springer International Publishing.Google Scholar
Bergman, S. M., Fearrington, M. E., Davenport, S. W. & Bergman, J. Z. (2011). Millennials, narcissism, and social networking: What narcissists do on social networking sites and why. Personality and Individual Differences, 50, 706–711.CrossRefGoogle Scholar
Berkelaar, B. L. (2014). Cybervetting, online information, and personnel selection: New transparency expectations and the emergence of a digital social contract. Management Communication Quarterly, 28(4), 479–506.CrossRefGoogle Scholar
Bertrand, M., & Mullainathan, S. (2004). Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination. American Economic Review, 94(4), 991–1013.CrossRefGoogle Scholar
Bonds-Raacke, J., & Raacke, J. (2010). MySpace and Facebook: Identifying dimensions of uses and gratifications for friend networking sites. Individual Differences Research, 8(1), 27–33.Google Scholar
Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history and scholarship. Journal of Computer Mediated Education, 13(1), article 11.Google Scholar
Bozarth, J. (2010). Social media for trainers: Techniques for enhancing and extending learning. Pfeiffer.Google Scholar
Brown, V. R., & Vaughn, E. D. (2011). The writing on the (Facebook) wall: The use of social networking sites in hiring decisions. Journal of Business and Psychology, 26(2), 219.CrossRefGoogle Scholar
Caers, R., & Castelyns, V. (2011). LinkedIn and Facebook in Belgium: The influences and biases of social network sites in recruitment and selection procedures. Social Science Computer Review, 29, 437–448. https://doi.org/10.1177/0894439310386567CrossRefGoogle Scholar
CareerBuilder. (2009). Forty-five percent of employers use social networking sites to research job candidates, CareerBuilder survey finds: Career expert provides dos and don’ts for job seekers on social networking. Press Releases. www.careerbuilder.com/share/aboutus/pressreleasesdetail.aspx?id=pr519&sd=8/19/2009&ed=12/31/2009Google Scholar
CareerBuilder. (2018, 9 Aug). More Than Half of Employers Have Found Content on Social Media That Caused Them NOT to Hire a Candidate, according to Recent CareerBuilder Survey. http://press.careerbuilder.com/2018-08-09-More-Than-Half-of-Employers-Have-Found-Content-on-Social-Media-That-Caused-Them-NOT-to-Hire-a-Candidate-According-to-Recent-CareerBuilder-SurveyGoogle Scholar
Chiang, J. K. H., & Suen, H. Y. (2015). Self-presentation and hiring recommendations in online communities: Lessons from LinkedIn. Computers in Human Behavior, 48, 516–524.CrossRefGoogle Scholar
Chu, T. H. (2020). A meta-analytic review of the relationship between social media use and employee outcomes. Telematics and Informatics, 50, 101379.CrossRefGoogle Scholar
Cober, R. T., Brown, D. J., Blumental, A. J., Doverspike, D., & Levy, P. (2000). The quest for the qualified job surfer: It’s time the public sector catches the wave. Public Personnel Management, 29(4), 479–496.CrossRefGoogle Scholar
Coker, B. L. S. (2011). Freedom to surf: The positive effects of workplace Internet leisure browsing. New Technology Work and Employment, 26(3), 238–247.CrossRefGoogle Scholar
Collmus, A. B., Armstrong, M. B., & Landers, R. N. (2016). Game-thinking within social media to recruit and select job candidates. In Landers, R. N. & Schmidt, G. B. (Eds.), Social media in employee selection and recruitment: Theory, practice, and current challenges (pp. 103–124). Springer International Publishing.Google Scholar
Davison, H. K., Bing, M. N., Kluemper, D. H., & Roth, P. L. (2016). Social media as a personnel selection and hiring resource: Reservations and recommendations. In Landers, R. N., & Schmidt, G. B. (Eds.), Social media in employee selection and recruitment: Theory, practice and current challenges (pp. 15–42). Springer International Publishing.Google Scholar
Davison, H. K., Maraist, C., & Bing, M. N. (2011a). Friend or foe? The promise and pitfalls of using social networking sites for HR decisions. Journal of Business and Psychology, 26(2), 153–159.CrossRefGoogle Scholar
Davison, H. K., Maraist, C. C., Hamilton, R. H., Bing, M. N. (2011b). To screen or not to screen? Using the Internet for selection decisions. Employee Responsibilities and Rights Journal, 24, 1–21.CrossRefGoogle ScholarPubMed
Dreher, S. (2014). Social media and the world of work a strategic approach to employees’ participation in social media. Corporate Communications: An International Journal, 19(4), 344–356.CrossRefGoogle Scholar
Drouin, M., O’Connor, K. W., Schmidt, G. B., & Miller, D. A. (2015). Facebook fired: Legal perspectives and young adults’ opinions on the use of social media in hiring and firing decisions. Computers in Human Behavior, 46, 123–128.CrossRefGoogle Scholar
Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends”: Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12(4), 1143–1168.CrossRefGoogle Scholar
Ellison, N. B., Steinfield, C., & Lampe, C. (2011). Connection strategies: Social capital implications of Facebook-enabled communication practices. New Media & Society, 13(6), 873–892.CrossRefGoogle Scholar
Ellison, N. B., Gibbs, J. L., & Weber, M. S. (2015). The use of enterprise social network sites for knowledge sharing in distributed organizations: The role of organizational affordances. American Behavioral Scientist, 59(1), 103–123.CrossRefGoogle Scholar
Flynn, N. (2012). The social media handbook: Policies and best practices to effectively manage your organization’s social media presence, posts, and potential risks. PfeifferGoogle Scholar
Funk, L. (2007, September 19). Women on Facebook think provocative is empowering. USA Today, p. A11.Google Scholar
Goldberg, L. (1990). An alternative “description of personality”: The Big Five factor structure. Journal of Personality and Social Psychology, 59, 1216–1229.CrossRefGoogle ScholarPubMed
Gosling, S. D., Augustine, A. A., Vazire, S., Holtzman, N., & Gaddis, S. (2011). Manifestations of personality in online social networks: Self-reported Facebook-related behaviors and observable profile information. Cyberpsychology, Behavior, and Social Networking, 14(9), 483–488.CrossRefGoogle ScholarPubMed
Gosling, S. D., Gaddis, S., & Vazire, S. (2007, March). Personality impressions based on Facebook profiles. Paper presented at the International Conference on Weblogs and Social Media, Boulder, CO.Google Scholar
Grasmuck, S., Martin, J., & Zhao, S. (2009). Ethno-racial identity displays on Facebook. Journal of Computer-Mediated Communication, 15(1), 158–188.CrossRefGoogle Scholar
Green, R. K. (2013, Aug 7). The Social Media Effect: Are You Really Who You Portray Online? Huffington Post. www.huffpost.com/entry/the-social-media-effect-a_b_3721029Google Scholar
Guilfoyle, S., Bergman, S. M., Hartwell, C., & Powers, J. (2016). Social media, big data, and employment decisions: Mo’ Data, Mo’ Problems? In Landers, R. N. & Schmidt, G. B. (Eds.), Social media in employee selection and recruitment: Theory, practice, and current challenges (pp. 127–155). Springer International Publishing.Google Scholar
Guion, R. M. (2011). Assessment, measurement, and prediction for personnel decisions. Routledge.CrossRefGoogle Scholar
Hargittai, E. (2007). Whose space? Differences among users and non-users of social network sites. Journal of Computer-Mediated Communication, 13, 267–297.CrossRefGoogle Scholar
Hargittai, E., & Hinnant, A. (2008). Digital inequality: Differences in young adults’ use of the Internet. Communication Research, 35(5), 602–621.CrossRefGoogle Scholar
Hargittai, E., & Hsieh, Y. P. (2010a). From dabblers to omnivores: A typology of social network site usage. In Papacharissi, Z. (Ed.), A networked self (pp. 146–168). Routledge.Google Scholar
Hargittai, E., & Hsieh, Y. P. (2010b). Predictors and consequences of social network site usage. Information, Communication and Society, 13, 515–536.CrossRefGoogle Scholar
Harper, S. R. (16 Jun 2020). Corporations say they support Black Lives Matter. Their employees doubt them. The Washington Post. www.washingtonpost.com/outlook/2020/06/16/corporations-say-they-support-black-lives-matter-their-employees-doubt-them/Google Scholar
Hickman, A. & Robison, J. (24 April 2020). Remote Work Trends to Guide High Performance During COVID-19. Gallup. www.gallup.com/workplace/309170/remote-work-trends-guide-high-performance-during-covid.aspx.Google Scholar
Hill, A. (2008). BT enterprise 2.0: Social media tools as an aid to learning and collaboration in the workplace, for the digital-generation and beyond. Case study from the career innovation group. http://richarddennison.files.wordpress.com/2008/09/ci-digital-generation-bt.pdfGoogle Scholar
Holley, P. (2015, May 4). Day-care employee fired for Facebook post saying she hates “being around a lot of kids”. Washington Post. www.washingtonpost.com/news/morning-mix/wp/2015/05/04/day-care-employee-fired-for-facebook-post-noting-she-hates-being-around-a-lot-of-kids/Google Scholar
Huffpost. (2013, November 04). This Boston Marathon Bombing Victim Costume Couldn’t Be More Horrible. Huffpost. www.huffpost.com/entry/boston-marathon-victim-costume_n_4208720Google Scholar
Judge, T., & Erez, A. (2007). Interaction and intersection: The constellation of emotional stability and extraversion in predicting performance. Personnel Psychology, 60, 573–596.CrossRefGoogle Scholar
Jurkowitz, M., & Mitchell, A. (2020, August 27). Americans who get news mostly through social media are least likely to follow coronavirus coverage. www.journalism.org/2020/03/25/americans-who-primarily-get-news-through-social-media-are-least-likely-to-follow-covid-19-coverage-most-likely-to-report-seeing-made-up-news/Google Scholar
Karl, K. A., & Peluchette, J. V. (2011). “Friending” professors, parents and bosses: A Facebook connection conundrum. Journal of Education for Business, 86(4), 214–222.CrossRefGoogle Scholar
Karl, K., Peluchette, J., & Schlaegel, C. (2010). Who’s posting Facebook faux pas? A cross-cultural examination of personality differences. International Journal of Selection and Assessment, 18, 174–186.CrossRefGoogle Scholar
Kemp, S. (2020, July 21). Digital 2020: July Global Statshot. https://datareportal.com/reports/digital-2020-july-global-statshotGoogle Scholar
Kluemper, D. H. (2013). Social network screening: Pitfalls, possibilities, and parallels in employment selection. Advanced Series in Management, 12, 1–21.Google Scholar
Kluemper, D. H., Mitra, A., & Wang, S. (2016). Social media use in HRM. Personnel and Human Resources Management, 34, 153–207.CrossRefGoogle Scholar
Kluemper, D. H., & Rosen, P. A. (2009). Future employment selection methods: Evaluating social networking web sites. Journal of Managerial Psychology, 24(6), 567–580.CrossRefGoogle Scholar
Kluemper, D. H., Rosen, P. A., & Mossholder, K. (2012). Social networking websites, personality ratings, and the organizational context: More than meets the eye. Journal of Applied Social Psychology, 42(5), 1143–1172.CrossRefGoogle Scholar
Lampe, C., Ellison, N., & Steinfield, C. (2006). A Face(book) in the crowd: Social searching vs. social browsing. Paper presented at the ACM Special Interest Group on Computer-Supported Cooperative Work, Banff, AB, Canada.Google Scholar
Lampe, C., Ellison, N., & Steinfield, C. (2008). Changes in use and perception of Facebook. In Proceedings of the 2008 ACM Conference on Computer Supported Cooperative Work (pp. 435–444). ACM.Google Scholar
Lampinen, A., Tamminen, S., & Oulasvirta, A. (2009). “All my people right here, right now”: Management of group co-presence on a social networking site. In Proceedings of the ACM 2009 International Conference on Supporting Group Work (GROUP ’09) (pp. 281–290). ACM.CrossRefGoogle Scholar
Landers, R. N., Brusso, R. C., Cavanaugh, K. J., & Collmus, A. B. (2016). A primer on theory-driven web scraping: Automatic extraction of big data from the Internet for use in psychological research. Psychological Methods, 21(4), 475–492.CrossRefGoogle ScholarPubMed
Landers, R. N., & Schmidt, G. B. (2016a). Social media in employee selection and recruitment: An overview. In Landers, R. N. & Schmidt, G. B. (Eds.), Social media in employee selection and recruitment: Theory, practice, and current challenges (pp. 3–14). Springer International Publishing.Google Scholar
Landers, R. N., & Schmidt, G. B. (2016b). Social media in employee selection and recruitment: Current knowledge, unanswered questions, and future directions. In Landers, R. N. & Schmidt, G. B. (Eds.), Social media in employee selection and recruitment: Theory, practice, and current challenges (pp. 343–367). Springer International Publishing.Google Scholar
Leftheriotis, I., & Giannakos, M. N. (2014). Using social media for work: Losing your time or improving your work? Computers in Human Behavior, 31, 134–142.CrossRefGoogle Scholar
Leidner, D., Koch, H., & Gonzalez, E. (2010). Assimilating generation Y IT new hires into USAA’s workforce: The role of an enterprise 2.0 system. MIS Quarterly Executive, 9, 229–242.Google Scholar
Leonardi, P. M., Huysman, M., & Steinfield, C. (2013). Enterprise social media: Definition, history, and prospects for the study of social technologies in organizations. Journal of Computer-Mediated Communication, 19(1), 1–19.CrossRefGoogle Scholar
Lieber, C. (2018, November 28). How and why do influencers make so much money? The head of an influencer agency explains. Vox. www.vox.com/the-goods/2018/11/28/18116875/influencer-marketing-social-media-engagement-instagram-youtubeGoogle Scholar
Lievens, F., & Harris, M. M. (2003). Research on Internet recruiting and testing: Current status and future directions. International Review of Industrial and Organizational Psychology, 18, 131–166.Google Scholar
Lieu, D. (2011). Hispanics and Blacks more likely than Whites to support causes on line. Chronicle of Philanthropy, June. www.philanthropy.com/article/HispanicsBlacks-More/227043Google Scholar
Liu, D. & Campbell, W. K. (2017). The Big Five personality traits, Big Two metatraits and social media: A meta-analysis. Journal of Research in Personality, 70, 229–240.CrossRefGoogle Scholar
Lynch, C. G. (2008, June 12). Lockheed Martin shows off internal social software platform. CIO. www.cio.com/article/393264/Lockheed_Martin_Shows_Off_Internal_Social_Software_PlatformGoogle Scholar
Madani, D., & Radford, M. (2020, May 27). White woman fired after calling NYPD on black man who asked her to leash her dog in Central Park. NBC News. www.nbcnews.com/news/us-news/white-woman-fired-job-after-calling-nypd-black-man-who-n1215016Google Scholar
Martineau, P. (2019, December 6). The WIRED guide to influencers: Everything you need to know about engagement, power likes, sponcon, and trust. WIRED. www.wired.com/story/what-is-an-influencer/Google Scholar
Massiah, A. (2019, October 4). Woman in swimsuit photo-shamed by potential employer. BBC News. www.bbc.com/news/blogs-trending-49931273Google Scholar
McFarland, L. A. & Ployhart, R. E. (2015). Social media in organizations: A theoretical framework to guide research and practice. Journal of Applied Psychology, 100(6), 1653–1677.CrossRefGoogle ScholarPubMed
Mehdizadeh, S. (2010). Self-presentation 2.0: Narcissism and self-esteem on Facebook. Cyberpsychology, Behavior, and Social Networking, 13(4), 357–364.CrossRefGoogle ScholarPubMed
Minocha, S. (2009). An empirically-grounded study on the effective use of social software in education. Education & Training, 51, 381–394.CrossRefGoogle Scholar
Moqbel, M., Nevo, S., & Kock, N. (2013). Organizational members’ use of social networking sites and job performance: An exploratory study. Information Technology & People, 26(3), 240–264.CrossRefGoogle Scholar
Muscanell, N. L., & Guadagno, R. E. (2012). Make new friends or keep the old: Gender and personality differences in social networking use. Computers in Human Behavior, 28, 107–112.CrossRefGoogle Scholar
Nadkarni, A., & Hofmann, S. G. (2012). Why do people use Facebook? Personality and Individual Differences, 52, 243–249.CrossRefGoogle ScholarPubMed
NLRB (2020). The NLRB and Social Media. National Labor Relations Board. www.nlrb.gov/about-nlrb/rights-we-protect/your-rights/the-nlrb-and-social-mediaGoogle Scholar
Nov, O., Naaman, M., & Ye, C. (2010). Analysis of participation in an online photo sharing community: A multidimensional perspective. Journal of the American Society for Information Science and Technology, 61, 555–566.CrossRefGoogle Scholar
O’Brien, J. (2014, June 11). Big data is changing the game for recruiters. Mashable. http://mashable.com/2014/06/11/big-data-recruiting/Google Scholar
O’Connor, K. W., & Schmidt, G. B. (2015). “Facebook fired”: Legal standards for social media based terminations of K-12 public school teachers. Journal of Workplace Rights (Sage Open), 5 (1), 1–11.Google Scholar
O’Connor, K. W., Schmidt, G. B., & Drouin, M. (2016). Helping workers understand and follow social media policies. Business Horizons, 59, 205–211.CrossRefGoogle Scholar
Ollington, N., Gibb, J., & Harcourt, M. (2013). Online social networks: An emergent recruiter tool for attracting and screening. Personnel Review, 42(3), 248–265.CrossRefGoogle Scholar
Peluchette, J., & Karl, K. (2008). Social networking profiles: An examination of student attitudes regarding use and appropriateness of content. CyberPsychology and Behavior, 11(1), 95–97.CrossRefGoogle ScholarPubMed
Peluchette, J., & Karl, K. (2010). Examining students’ intended image on Facebook: “What were they thinking?!” Journal of Education for Business, 85, 30–37.CrossRefGoogle Scholar
Perrin, A., & Anderson, M. (2019, April 10). Share of U.S. adults using social media, including Facebook, is mostly unchanged since 2018. Pew Research Center. www.pewresearch.org/facttank/2019/04/10/share-of-u-s-adults-using-social-media-including-facebook-is-mostly-unchanged-since-2018/Google Scholar
Raacke, J., & Bonds-Raacke, J. (2008). MySpace and Facebook: Applying the uses and gratifications theory to exploring friend-networking sites. Cyberpsychology & Behavior, 11(2), 169–174.CrossRefGoogle ScholarPubMed
Rhee, H. and Kim, S. (2015). Effects of breaks on regaining vitality at work: An empirical comparison of “conventional” and “smart phone” breaks. Computers in Human Behavior, 57, 160–167.CrossRefGoogle Scholar
Robertson, B. W., & Kee, K. F. (2017). Social media at work: The roles of job satisfaction, employment status, and Facebook use with co-workers. Computers in Human Behavior, 70, 191–196.CrossRefGoogle Scholar
Roth, P. L., Bobko, P., Van Iddekinge, C. H., & Thatcher, J. B. (2016). Social media in employee-selection-related decisions: A research agenda for uncharted territory. Journal of Management, 42(1), 269–298.CrossRefGoogle Scholar
Roulin, N., & Bangerter, A. (2013). Social networking websites in personnel selection: A signaling perspective on recruiters’ and applicants’ perceptions. Journal of Personnel Psychology, 12(3), 143–151.CrossRefGoogle Scholar
Roulin, N., & Levashina, J. (2019). LinkedIn as a new selection method: Psychometric properties and assessment approach. Personnel Psychology, 72(2), 187–211.CrossRefGoogle Scholar
Rynes, S. L. (1991). Recruitment, job choice, and post-hire consequences: A call for new research directions. In Dunnette, M. D. & Hough, L. M. (Eds.), Handbook of Industrial and Organizational Psychology (vol. 2, 2nd ed., pp. 399–444). Consulting Psychologists Press.Google Scholar
Schmidt, G. B., & O’Connor, K. W. (2015). Fired for Facebook: Using NLRB guidance to craft appropriate social media policies. Business Horizons, 58, 571–579.CrossRefGoogle Scholar
Schmidt, G. B. & O’Connor, K. W. (2016). Legal concerns when considering social media data in selection. In Landers, R. N. & Schmidt, G. B. (Eds.), Social media in employee selection and recruitment: Theory, practice, and current challenges (pp. 265–288). Springer International Publishing.Google Scholar
Settanni, M., Azucar, D., & Marengo, D. (2018). Predicting individual characteristics from digital traces on social media: A meta-analysis. Cyberpsychology, Behavior, and Social Networking, 21(4), 217–228.CrossRefGoogle ScholarPubMed
SHRM. (2017, September 20). Using social media for talent acquisition – recruitment and screening. www.shrm.org/hr-today/trends-and-forecasting/research-and-surveys/pages/social-media-recruiting-screening-2015.aspx.Google Scholar
Sitzmann, T., Kraiger, K., Stewart, D., & Wisher, R. (2006). The comparative effectiveness of web‐based and classroom instruction: A meta‐analysis. Personnel Psychology, 59(3), 623–664.CrossRefGoogle Scholar
Slovensky, R., & Ross, W. H. (2012). Should human resource managers use social media to screen job applicants? Managerial and legal issues in the USA. Info, 14, 55–69.CrossRefGoogle Scholar
Steinfield, C., Ellison, N. B., & Lampe, C. (2008). Social capital, self-esteem, and use of online social network sites: A longitudinal analysis. Journal of Applied Developmental Psychology, 29(6), 434–445.CrossRefGoogle Scholar
Stone, B., & Brown, R. (2006, August 28). Web of risks: Students adore social-networking sites like Facebook, but indiscreet postings can mean really big trouble. Newsweek, 148(8/9), 76–77.Google Scholar
Timimi, F. K. (2013). The shape of digital engagement health care and social media. The Journal of Ambulatory Care Management, 36(3), 187–192CrossRefGoogle ScholarPubMed
Van Birgelen, M. J., Wetzels, M. G., & van Dolen, W. M. (2008). Effectiveness of corporate employment web sites. International Journal of Manpower, 29(8), 731–751.CrossRefGoogle Scholar
Van Hoye, G., & Lievens, F. (2007). Investigating web‐based recruitment sources: Employee testimonials vs word‐of‐mouse. International Journal of Selection and Assessment, 15(4), 372–382.CrossRefGoogle Scholar
Van Iddekinge, C. H., Lanivich, S. E., Roth, P. L., & Junco, E. (2016). Social media for selection? Validity and adverse impact potential of a Facebook-based assessment. Journal of Management, 42(7), 1811–1835.CrossRefGoogle Scholar
Van Puijenbroek, T., Poell, R. F., Kroon, B., & Timmerman, V. (2014). The effect of social media use on work‐related learning. Journal of Computer-Assisted Learning, 30(2), 159–172.CrossRefGoogle Scholar
Vasalou, A., Joinson, A. N., & Courvoisier, D. (2010). Cultural differences, experience with social networks and the nature of “true commitment” in Facebook. International Journal of Human-Computer Studies, 68(10), 719–728.CrossRefGoogle Scholar
Vaughn, D., Petersen, N., & Gibson, C. (2019). The use of social media in staffing. In Landers, R. (Ed.), The Cambridge handbook of technology and employee behavior (pp. 232–268). Cambridge University Press.CrossRefGoogle Scholar
Vazire, S., & Gosling, S. D. (2004). e-Perceptions: Personality impressions based on personal websites. Journal of Personality and Social Psychology, 87(1), 123–132.CrossRefGoogle ScholarPubMed
Way, K. (2020, 29 January). Meet the firefighter who got fired for fire Instagram content. Vice Magazine. www.vice.com/en_us/article/pkeaqz/presley-pritchard-fitness-instagram-discrimination-lawsuitGoogle Scholar
Weidner, N., O’Brien, K. E., & Wynne, K. T. (2016). Social media use: Antecedents and outcomes of sharing. In Landers, N. R. & Schmidt, B. G. (Eds.), Social media in employee selection and recruitment: Theory, practice, and current challenges (pp. 79–101). Springer International Publishing.Google Scholar
Willyerd, K. (2012). Social tools can improve employee onboarding. Harvard Business Review. https://hbr.org/2012/12/social-tools-can-improve-e.Google Scholar
Wilson, R. E., Gosling, S. D., & Graham, L. T. (2012). A review of Facebook research in the social sciences. Perspectives on Psychological Science, 7(3), 203–220.CrossRefGoogle ScholarPubMed
Yan, J. (2011). Social media in branding: Fulfilling a need. Journal of Brand Management, 18, 688–696.CrossRefGoogle Scholar
Zacher, H., Brailsford, H. A., & Parker, S. L. (2015). Micro-breaks matter: A diary study on the effects of energy management strategies on occupational well-being. Journal of Vocational Behavior, 85, 287–297.CrossRefGoogle Scholar
Zetlin, M. (2018, August 23). How one young woman lost her dream job and learned the hard way to be more cautious on Twitter. Inc.com. www.inc.com/minda-zetlin/nasa-intern-homer-hickam-naomi-h-profane-tweet-twitter-internship.htmlGoogle Scholar
Zhang, L., Van Iddekinge, C. H., Arnold, J. D., Roth, P. L., Lievens, F., Lanivich, S. E., & Jordan, S. L. (2020). What’s on job seekers’ social media sites? A content analysis and effects of structure on recruiter judgments and predictive validity. Journal of Applied Psychology. https://doi.org/10.1037/apl0000490CrossRefGoogle Scholar
Zhang, X., Ma, L., Xu, B., & Xu, F. (2019). How social media usage affects employees’ job satisfaction and turnover intention: An empirical study in China. Information & Management, 56 (6), 103136. doi: https://doi.org/10.1016/j.im.2018.12.004CrossRefGoogle Scholar
Zhang, Z. J. (2012). A social software strategy for knowledge management and organization culture. OR Insight, 25, 60–79.CrossRefGoogle Scholar
Zickar, M. J. (2020). Measurement Development and Evaluation. Annual Review of Organizational Psychology and Organizational Behavior, 7, 213–232.CrossRefGoogle Scholar
References
Abdu, S. D., Mohamad, B., & Muda, S. (2017). Youth online political participation: The role of Facebook use, interactivity, quality information and political interest. In SHS Web of Conferences (Vol. 33, p. 1–10). EDP Sciences.Google Scholar
Alhabash, S., & Ma, M. (2017). A tale of four platforms: Motivations and uses of Facebook, Twitter, Instagram, and Snapchat among college students? Social Media + Society, 3(1), 1–13.CrossRefGoogle Scholar
Andolina, M., Keeter, S., Zukin, C., & Jenkins, K. (2003). A guide to the index of civic and political engagement. College Park, MD: The Center for Information and Research on Civic Learning and Engagement.Google Scholar
Anspach, N. M., Jennings, J. T., & Arceneaux, K. (2019). A little bit of knowledge: Facebook’s news feed and self-perceptions of knowledge. Research and Politics, 6(1), 1–9.CrossRefGoogle Scholar
Bakker, T. P., & de Vreese, C. H. (2011). Good news for the future? Young people, internet use, and political participation. Communication Research, 38(4), 451–470.CrossRefGoogle Scholar
Bakshy, E., Messing, S., & Adamic, L.A .(2015). Exposure to ideologically diverse news and opinion on Facebook. Science, 348(6239), 1130–1132.CrossRefGoogle ScholarPubMed
Becker, A. B., & Copeland, L. (2016). Networked publics: How connective social media use facilitates political consumerism among LGBT Americans. Journal of Information Technology & Politics, 13(1), 22–36.CrossRefGoogle Scholar
Bennett, W. L., & Segerberg, A. (2013). The logic of connective action: Digital media and the personalization of contentious politics. Cambridge University Press.CrossRefGoogle Scholar
Bimber, B., & Copeland, L. (2013). Digital media and traditional political participation over time in the US. Journal of Information Technology & Politics, 10(2), 125–137.CrossRefGoogle Scholar
Blumler, J. G., & McQuail, D. (1969. Television in politics: Its uses and influence. Faber and Faber.Google Scholar
Boczkowski, P. J., Mitchelstein, E., & Matassi, M. (2018). “News comes across when I’m in a moment of leisure”: Understanding the practices of incidental news consumption on social media. New Media & Society, 20, 3523–3539.CrossRefGoogle Scholar
Bode, L. (2017). Gateway political behaviors: The frequency and consequences of low-cost political engagement on social media. Social Media Society, 3(4), 1–10.Google Scholar
Bode, L., Vraga, E. K., Borah, P., & Shah, D. V. (2014). A new space for political behavior: Political social networking and its democratic consequences. Journal of Computer-Mediated Communication, 19(3), 414–429.CrossRefGoogle Scholar
Bond, R. M., & Sweitzer, M. D. (2018). Political homophily in a large-scale online communication network. Communication Research, 0093650218813655.Google Scholar
Boorstin, J. (2016, November 8). Facebook, Snapchat and Twitter played a bigger role than ever in the election. CNBC. Retrieved from www.cnbc.com/2016/11/08/facebook-snapchat-and-twitter-played-a-bigger-role-than-ever-in-the-election.htmlGoogle Scholar
Borgatti, S. P., & Cross, R. (2003). A relational view of information seeking and learning in social networks. Management Science, 49(4), 432–445.CrossRefGoogle Scholar
Bossetta, M. (2018). The digital architectures of social media: Comparing political campaigning on Facebook, Twitter, Instagram, and Snapchat in the 2016 U.S. election. Journalism and Mass Communication Quarterly, 95(2), 471–496.CrossRefGoogle Scholar
Boulianne, S. (2009). Does Internet use affect engagement? A meta-analysis of research. Political Communication, 26(2), 193–211.CrossRefGoogle Scholar
Boulianne, S. (2015). Social media use and participation: A meta-analysis of current research. Information, Communication & Society, 18(5), 524–538.CrossRefGoogle Scholar
Boulianne, S. (2016). Online news, civic awareness, and engagement in civic and political life. New Media & Society, 18(9), 1840–1856.CrossRefGoogle Scholar
Boulianne, S. (2019). Revolution in the making? Social media effects across the globe. Information, Communication & Society, 22 (1), 39–54.CrossRefGoogle Scholar
Boulianne, S. (2020). Twenty years of digital media effects on civic and political participation. Communication Research, 47(7), 947–966.CrossRefGoogle Scholar
Boulianne, S., Koc-Michalska, K., & Bimber, B. (2020). Mobilizing media: Comparing TV and social media effects on protest mobilization. Information, Communication & Society, 23(5), 642–664.CrossRefGoogle Scholar
Boulianne, S., & Theocharis, Y. (2020). Young people, digital media and engagement: A metaanalysis of research. Social Science Computer Review, 38(2), 111–127.CrossRefGoogle Scholar
Boyd, D. (2008) Taken out of context: American teen sociality in networked publics. PhD Thesis, University of California–Berkeley.Google Scholar
Boyd, D. (2009, February 26). Social media is here to stay… Now what? Microsoft Research Tech Fest. Retrieved from www.danah.org/papers/talks/MSRTechFest2009.htmlGoogle Scholar
Boyd, D. (2010). Social network sites as networked publics: Affordances, dynamics, and implications. In Papacharissi, Z. (Ed.), Networked self: Identity, community, and culture on social network sites (pp. 39–58). Routledge.Google Scholar
Boyd, D. (2014, March 21). Why Snapchat is valuable: It’s all about attention. Retrieved from www.linkedin.com/pulse/20140321152822-79695780-why-snapchat-isvaluable-it-s-all-about-attentionGoogle Scholar
Boyd, D., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210–30.CrossRefGoogle Scholar
Brady, H. (1999). Political participation. In Robinson, J. P., Shaver, P. R., & Wrightsman, L. S. (Eds.), Measures of political attitudes (pp. 737–801). Academic Press.Google Scholar
Brundidge, J., & Rice, R. E. (2009). Political engagement online: Do the information rich get richer and the like-minded more similar? In Andrew, C. & Howard, P. N. (Eds.), Routledge handbook of internet politics (144–156). Routledge.Google Scholar
Bucy, E. P. (2005). The media participation hypothesis. In McKinney, M. S., Kaid, L. L., Bystrom, D. G., & Carlin, D. B. (Eds.), Communicating politics: Engaging the public in democratic life (pp. 107–122). Peter Lang Publishing.Google Scholar
Bucy, E. P., & Gregson, K. S. (2001). Media participation: A legitimizing mechanism of mass democracy. New Media & Society, 3(3), 359–382.Google Scholar
Bucy, E. P., & Groshek, J. (2018). Empirical support for the media participation hypothesis: Trends across presidential elections, 1992–2012. New Media & Society, 20(5), 1889–1909.CrossRefGoogle Scholar
Buozis, M. (2019). Doxing or deliberative democracy? Evidence and digital affordances in the Serial subReddit. Convergence, 25(3), 357–373.CrossRefGoogle Scholar
Chan, M. (2014). Social identity gratifications of social network sites and their impact on collective action participation. Asian Journal of Social Psychology, 17, 229–235.CrossRefGoogle Scholar
Chan, M. (2016). Social network sites and political engagement: Exploring the impact of Facebook connections and uses on political protest and participation. Mass Communication & Society, 19(4), 430–451.CrossRefGoogle Scholar
Cho, J., Shah, D. V., McLeod, J. M., McLeod, D. M., Scholl, R. M., & Gotlieb, M. R. (2009). Campaigns, reflection, and deliberation: Advancing an O-S-R-O-R model of communication effects. Communication Theory, 19, 66–88CrossRefGoogle Scholar
Choi, D. H., & Shin, D. H. (2017). A dialectic perspective on the interactive relationship between social media and civic participation: The moderating role of social capital. Information, Communication & Society, 20(2), 151–166.CrossRefGoogle Scholar
Conroy, M., Feezell, J. T., & Guerrero, M. (2012). Facebook and political engagement: A study of online political group membership and offline political engagement. Computers in Human Behavior, 28, 1535–1546.CrossRefGoogle Scholar
Copeland, L., & Boulianne, S. (2020). Political consumerism: A meta-analysis. International Political Science Review, 0192512120905048.Google Scholar
Copeland, L., Hasell, A., & Bimber, B. (2016). Collective action frames, advocacy organizations, and protests over same-sex marriage. International Journal of Communication, 10, 23.Google Scholar
De Moor, J. (2017). Lifestyle politics and the concept of political participation. Acta Politica, 52(2), 179–197.CrossRefGoogle Scholar
Dimitrova, D. V., Shehata, A., Strömbäck, J., & Nord, L. W. (2014). The effects of digital media on political knowledge and participation in election campaigns: Evidence from panel data. Communication research, 41(1), 95–118.CrossRefGoogle Scholar
Duffy, B. E., & Chan, N. K. (2019). “You never really know who’s looking”: Imagined surveillance across social media platforms. New Media & Society, 21(1), 119–138.CrossRefGoogle Scholar
Duman, S., & Locher, M. A. (2008). “So let’s talk. Let’s chat. Let’s start a dialog”: An analysis of the conversation metaphor employed in Clinton’s and Obama’s YouTube campaign clips. Multilingua, 27(3), 193–230.CrossRefGoogle Scholar
Edgerly, S., Vraga, E. K., Bode, L., Thorson, K., & Thorson, E. (2018). New media, new relationship to participation? A closer look at youth news repertoires and political participation. Journalism & Mass Communication Quarterly, 95, 192–212.CrossRefGoogle Scholar
Ellison, N. B., & Boyd, D. (2013). Sociality through social network sites. In The Oxford handbook of internet studies (pp. 151–172). Oxford University Press.Google Scholar
Ellison, N. B., Gibbs, J. L. & Weber, M. S. (2015). The use of enterprise social network sites for knowledge sharing in distributed organizations: The role of organizational affordances. American Behavioral Scientist, 59(1), 103–123.CrossRefGoogle Scholar
Ellison, N., & Vitak, J. (2015). Social media affordances and their relationship to social capital processes. In Sundar, S. (Ed.), The handbook of psychology of communication technology (pp. 205–227). Wiley-Blackwell.Google Scholar
Endres, K., & Panagopoulos, C. (2017). Boycotts, buycotts, and political consumerism in America. Research & Politics, 4(4), 2053168017738632.CrossRefGoogle Scholar
Evans, S. K., Pearce, K. E., Vitak, J., & Treem, J. W. (2017). Explicating affordances: A conceptual framework for understanding affordances in communication research. Journal of Computer-Mediated Communication, 22(1), 35–52.CrossRefGoogle Scholar
Eveland, W. P. (2004). The effect of political discussion in producing informed citizens: The roles of information, motivation and elaboration. Political Communication, 21, 177–193.CrossRefGoogle Scholar
Eveland, W. P., & Hively, M. H. (2009). Political discussion frequency, network size, and “heterogeneity” of discussion as predictors of political knowledge and participation. Journal of Communication, 59(2), 205–224.CrossRefGoogle Scholar
Foot, K. A., Schneider, S. M., & Cornfield, M. (2006). Web campaigning. MIT Press.CrossRefGoogle Scholar
Fox, S. (2013). Is it time to update the definition of political participation? Parliamentary Affairs, 67(2), 495–505.CrossRefGoogle Scholar
Gaver, W. (1991). Technology affordances. Proceedings of SIGCHI Conference on Human Factors in Computing Systems (pp. 79–84). ACM.CrossRefGoogle Scholar
Gerbaudo, P. (2015). Protest avatars as memetic signifiers: Political profile pictures and the construction of collective identity on social media in the 2011 protest wave. Information, Communication & Society, 18(8), 916–929.CrossRefGoogle Scholar
Gibson, J. J. (1986). The ecological approach to visual perception. Mahwah, NJ: Erlbaum.Google Scholar
Gil de Zúñiga, H., Ardèvol-Abreu, A., & Casero-Ripollés, A. (2021). WhatsApp political discussion, conventional participation and activism: Exploring direct, indirect and generational effects. Information, Communication & Society, 24(2), 201–218.CrossRefGoogle Scholar
Gil de Zúñiga, H. G., Barnidge, M., & Scherman, A. (2017). Social media social capital, offline social capital, and citizenship: Exploring asymmetrical social capital effects. Political Communication, 34(1), 44–68.CrossRefGoogle Scholar
Gil de Zúñiga, H., Copeland, L., & Bimber, B. (2014) Political consumerism: Civic engagement and the social media connection. New Media & Society, 16(3), 488–506.CrossRefGoogle Scholar
Gil de Zúñiga, H., & Diehl, T. (2019). News finds me perception and democracy: Effects on political knowledge, political interest, and voting. New Media & Society, 21(6), 1253–1271.CrossRefGoogle Scholar
Gil de Zúñiga, H., Jung, N., & Valenzuela, S. (2012). Social media use for news and individuals’ social capital, civic engagement and political participation. Journal of Computer-Mediated Communication, 17(3), 319–336CrossRefGoogle Scholar
Gil de Zúñiga, H., Molyneux, L., & Zheng, P. (2014). Social media, political expression, and political participation: Panel analysis of lagged and concurrent relationships. Journal of Communication, 64(4), 612–634.CrossRefGoogle Scholar
Gil de Zúñiga, H., Strauss, N., & Huber, B. (2020). The proliferation of the “news finds me” perception across societies. International Journal of Communication, 14, 29.Google Scholar
Gil de Zúñiga, H., Weeks, B., & Ardèvol-Abreu, A. (2017). Effects of the news-finds-me perception in communication: Social media use implications for news seeking and learning about politics. Journal of Computer-Mediated Communication, 22(3), 105–123.CrossRefGoogle Scholar
Gloric, K., Anderson, A., & West, R. (2018, June). How constraints affect content: The case of Twitter’s switch from 140 to 280 characters. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 12, No. 1).Google Scholar
Gladwell, M., (2010). Why the revolution will not be tweeted. The New Yorker. Retrieved from www.newyorker.com/reporting/2010/10/04/101004fa_fact_gladwe.Google Scholar
Gotlieb, M. R., & Cheema, S. E. (2017). From consumer to producer: Motivations, internet use, and political consumerism. Information, Communication & Society, 20, 570–586.CrossRefGoogle Scholar
Graham, T., Broersma, M., Hazelhoff, K. & van’t Haar, G. (2013). Between broadcasting political messages and interacting with voters: The use of Twitter during the 2010 UK General Election campaign. Information, Communication & Society, 16, 692–716.CrossRefGoogle Scholar
Greeno, J. (1994). Gibson’s affordances. Psychological Review, 101, 336–342.CrossRefGoogle ScholarPubMed
Halpern, D., & Gibbs, J. (2013). Social media as a catalyst for online deliberation? Exploring the affordances of Facebook and YouTube for political expression. Computers in Human Behavior, 29, 1159–1168.CrossRefGoogle Scholar
Halpern, D., Valenzuela, S., & Katz, J. E. (2017). We face, I tweet: How different social media influence political participation through collective and internal efficacy. Journal of Computer‐Mediated Communication, 22(6), 320–336.CrossRefGoogle Scholar
Hargreaves, I., & Thomas, J. (2002). New news, old news. London: Independent Television Commission/Broadcasting Standards Commission.Google Scholar
Harlow, S. (2019). Framing# Ferguson: A comparative analysis of media tweets in the US, UK, Spain, and France. International Communication Gazette, 81(6–8), 623–643.CrossRefGoogle Scholar
Harlow, S., & Johnson, T. (2011). Overthrowing the protest paradigm? How The New York Times, Global Voices and Twitter covered the Egyptian revolution. International Journal of Communication, 5, 1359–1374.Google Scholar
Harlow, S., Kilgo, D. K., Salaverría, R., & García-Perdomo, V. (2020). Is the whole world watching? Building a typology of protest coverage on social media from around the world. Journalism Studies.CrossRefGoogle Scholar
Harlow, S., Salaverría, R., Kilgo, D. K., & García-Perdomo, V. (2017). Protest paradigm in multimedia: Social media sharing of coverage about the crime of Ayotzinapa, Mexico. Journal of Communication, 67(3), 328–349.CrossRefGoogle Scholar
Heft, H. (1989). Affordances and the body: An intentional analysis of Gibson’s ecological approach to visual perception. Journal for the Theory of Social Behavior, 19, 1–30.CrossRefGoogle Scholar
Heiss, R., & Matthes, J. (2019). Does incidental exposure on social media equalize or reinforce participatory gaps? Evidence from a panel study. New Media & Society, 21(11–12), 2463–2482.CrossRefGoogle Scholar
Hermida, A. (2010). Twittering the news: The emergence of ambient journalism. Journalism Practice, 4(3), 297–308.CrossRefGoogle Scholar
Herzog, H. (1944). What do we really know about daytime serial listeners? In Lazarsfeld, P. F. & Stanton, F. N. (Eds.), Radio research 1943–1943 (pp. 3–33). Duell, Sloan & Pearce.Google Scholar
Holt, K., Shehata, A., Strömbäck, J., & Ljungberg, E. (2013). Age and the effects of news media attention and social media use on political interest and participation: Do social media function as leveler? European Journal of Communication, 28(1), 19–34.CrossRefGoogle Scholar
Howard, P. N., Duffy, A., Freelon, D., Hussain, M. M., Mari, W., & Maziad, M. (2011). Opening closed regimes: What was the role of social media during the Arab Spring? Available at SSRN 2595096.CrossRefGoogle Scholar
Hutchby, I. (2001). Technologies, texts and affordances. Sociology, 35(2), 441–456.CrossRefGoogle Scholar
Hutchby, I. & Barnett, S. (2005). Aspects of the sequential organization of mobile phone conversation. Discourse Studies, 7(2), 147–171.CrossRefGoogle Scholar
Jaidka, K., Zhou, A., & Lelkes, Y. (2019). Brevity is the soul of Twitter: The constraint affordance and political discussion. Journal of Communication, 69(4), 345–372.CrossRefGoogle Scholar
Jennings, K. M., & Zeitner, V. (2003). Internet use and civic engagement: A longitudinal analysis. Public Opinion Quarterly, 67(3), 311–334.CrossRefGoogle Scholar
Jensen, T. B., & Dyrby, S. (2013). Exploring affordances of Facebook as a social media platform in political campaigning. ECIS 2013 Completed Research, 40.Google Scholar
Johnson, O., Hall-Phillips, A., Chung, T. L., & Cho, H. (2019). Are you connected through consumption? The role of hashtags in political consumption. Social Media + Society, 5(4), 2056305119883427.CrossRefGoogle Scholar
Joyce, C. K. (2009). The blank page: Effects of constraint on creativity. University of California, Berkeley.Google Scholar
Kalsnes, B., Larsson, A. O., & Enli, G. (2017). The social media logic of political interaction: Exploring citizens’ and politicians’ relationship on Facebook and Twitter. First Monday, 22(2).Google Scholar
Kam, C. D., & Deichert, M. (2019). Boycotting, buycotting, and the psychology of political consumerism. Journal of Politics, 82(1), 72–88.CrossRefGoogle Scholar
Katz, E., Blumler, J., & Gurevitch, M. (1974). Utilization of mass communication by the individual. In Blumler, J. & Katz, E. (Eds.), The uses of mass communication: Current perspectives on gratifications research (pp. 19–34). Sage.Google Scholar
Kelm, O., & Dohle, M. (2018). Information, communication and political consumerism: How (online) information and (online) communication influence boycotts and buycotts. New Media & Society, 20(4), 1523–1542.CrossRefGoogle Scholar
Kilgo, D., & Harlow, S. (2019). Protests, media coverage, and a hierarchy of social struggle. International Journal of Press/Politics, 24(4), 508–530.Google Scholar
Kilgo, D. K., Harlow, S., García-Perdomo, V., Salaverría, R. (2018). From #Ferguson to#Ayotzinapa: Analyzing the differences in domestic and foreign protest news shared on social media. Mass Communication & Society, 21(5), 606–630.Google Scholar
Kilgo, D., & Mourão, R. R. (2019). Media effects and marginalized ideas: Relationships among media consumption and support for Black Lives Matter. International Journal of Communication, 13, 19.Google Scholar
Kim, S-H. (2007). Media use, social capital, and civic participation in South Korea. Journalism & Mass Communication Quarterly, 84, 477–494.CrossRefGoogle Scholar
Kim, Y., Chen, H. T., & De Zúñiga, H. G. (2013). Stumbling upon news on the Internet: Effects of incidental news exposure and relative entertainment use on political engagement. Computers in Human Behavior, 29(6), 2607–2614.CrossRefGoogle Scholar
Knoll, J., Matthes, J., & Heiss, R. (2018). The social media political participation model: A goal systems theory perspective. Convergence, 26(1), 135–156.CrossRefGoogle Scholar
Koren, M. 2017. The Silent Power of Live-Streaming Politics. The Atlantic. Retrieved from www.theatlantic.com/technology/archive/2017/06/comey-livestream-trump/529779/Google Scholar
Kreiss, D., Lawrence, R. G., & McGregor, S. G. (2018) In their own words: Political practitioner accounts of candidates, audiences, affordances, genres, and timing in strategic social media use, Political Communication, 35,(1), 8–31.CrossRefGoogle Scholar
Kümpel, A. S. (2020). The Matthew Effect in social media news use: Assessing inequalities in news exposure and news engagement on social network sites (SNS). Journalism, 21(8), 1083–1098.CrossRefGoogle Scholar
Kwak, H., Lee, C., Park, H., & Moon, S. (2010). What is Twitter, a social network or a news media? In Proceedings of the 19th International Conference on WorldWideWeb (pp. 591–600). ACM.CrossRefGoogle Scholar
Lalancette, M., & Raynauld, V. (2019). The power of political image: Justin Trudeau, Instagram, and celebrity politics. American Behavioral Scientist, 63(7), 888–924.CrossRefGoogle Scholar
Lee, F. L. F., Chen, H. T., & Chan, M. (2017). Social media use and university students’ participation in a large-scale protest campaign: The case of Hong Kong’s Umbrella movement. Telematics and Informatics, 34, 457–469.CrossRefGoogle Scholar
Lim, M. (2012). Clicks, cabs, and coffee houses: Social media and oppositional movements in Egypt, 2004–2011. Journal of Communication, 62(2), 231–248.CrossRefGoogle Scholar
Marwick, A. E., & Boyd, d. (2011) I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience. New Media & Society 13(1), 114–133.CrossRefGoogle Scholar
Matthes, J., Nanz, A., Stubenvoll, M., & Heiss, R. (2020). Processing news on social media. The political incidental news exposure model (PINE). Journalism, 1464884920915371.Google Scholar
Matsa, K. E., & Shearer, E. (2018). News use across social media platforms. Pew Research Center. Retrieved from: www.journalism.org/2018/09/10/news-use-across-social-media-platforms-2018/.Google Scholar
McQuail, D. (1994). The rise of media mass communication. In McQuail, D. (Ed.), Mass communication theory: An introduction (pp. 1–29). Sage.Google Scholar
Messing, S., & Westwood, S. J. (2014). Selective exposure in the age of social media: Endorsements Trump partisan source affiliation when selecting news online. Communication Research, 41(8), 1042–1063.CrossRefGoogle Scholar
Micheletti, M. (2010). Political virtue and shopping: Individuals, consumption, and collective action. Palgrave Macmillan.Google Scholar
Morozov, E. (2009, May 19). The brave new world of slacktivism. Foreign Policy, https://foreignpolicy.com/2009/05/19/the-brave-new-world-of-slacktivism/.Google Scholar
Mourão, R. R., Kilgo, D. K., & Sylvie, G. (2018). Framing Ferguson: The interplay of advocacy frames and journalistic frames in local and national newspaper coverage of Michael Brown. Journalism. 1464884918778722.Google Scholar
Naderer, B., Heiss, R., & Matthes, J. (2020). The skilled and the interested: How personal curation skills increase or decrease exposure to political information on social media. Journal of Information Technology & Politics, 17(4), 452–460.CrossRefGoogle Scholar
Nagy, P., & Neff, G. (2015). Imagined affordance: Reconstructing a keyword for communication theory. Social Media + Society, 1(2). 1–9.CrossRefGoogle Scholar
Neuman, W. R., Just, M. R., & Crigler, A. N. (1992) Common knowledge: News and the construction of political meaning. University of Chicago Press.CrossRefGoogle Scholar
Newman, N., Fletcher, R. Schulz, A., Andi, S., & Nielsen, R. K. (2020). Digital news report 2020. Reuters Institute for the Study of Journalism.Google Scholar
Norris, P. (2000). A virtuous circle: Political communications in postindustrial societies. Cambridge University Press.CrossRefGoogle Scholar
O’Reilly, T. (2012). What is Web 2.0? Design patterns and business models for the next generation software. In Mandiberg, M. (Ed.), The social media reader (pp. 32–52). New York University Press.CrossRefGoogle Scholar
Oeldorf-Hirsch, A. (2018). The role of engagement in learning from active and incidental news exposure on social media. Mass Communication and Society, 21(2), 225–247.CrossRefGoogle Scholar
Oeldorf-Hirsch, A., & Sundar, S. S. (2015). Posting, commenting, and tagging: Effects of sharing news stories on Facebook. Computers in Human Behavior, 44, 240–249.CrossRefGoogle Scholar
Ohme, J. (2019). Updating citizenship? The effects of digital media use on citizenship understanding and political participation. Information, Communication & Society, 22(13), 1903–1928.CrossRefGoogle Scholar
Ohme, J., de Vreese, C. H., & Albæk, E. (2018). From theory to practice: How to apply van Deth’s conceptual map in empirical political participation research. Acta Politica, 53(3), 367–390.CrossRefGoogle Scholar
Oser, J. & Boulianne, S. (2020). Reinforcement effects between digital media use and political participation: A meta-analysis of repeated-wave panel data. Public Opinion Quarterly, Online First, 1–11.CrossRefGoogle Scholar
Oz, M., Zheng, P., & Chen, G. M. (2018). Twitter versus Facebook: Comparing incivility, impoliteness, and deliberative attributes. New Media & Society, 20(9), 3400–3419.CrossRefGoogle Scholar
Park, C. S., & Kaye, B. K. (2020). What’s this? Incidental exposure to news on social media, news-finds-me perception, news efficacy, and news consumption. Mass Communication & Society, 157–180.CrossRefGoogle Scholar
Park, N., Kee, K. F., & Valenzuela, S. (2009). Being immersed in social networking environment: Facebook groups, uses and gratifications, and social outcomes. Cyberpsychology & Behavior, 12(6), 729–733.CrossRefGoogle ScholarPubMed
Pingree, R. J. (2007). How messages affect their senders: A more general model of message effects and implications for deliberation. Communication Theory, 17(4), 439–461.CrossRefGoogle Scholar
Piper, N. (2016, August 25). Snapchat lures more campaign spending as candidates court young voters. Bloomberg. Retrieved from www.bloomberg.com/news/articles/2016-08-25/snapchat-lures-more-campaign-spending-as-candidates-court-young-votersGoogle Scholar
Piwek, L., & Joinson, A. (2016). “What do they Snapchat about?” Patterns of use in time-limited instant messaging service. Computers in Human Behavior, 54, 358–367.CrossRefGoogle Scholar
Postigo, H. (2016). The socio-technical architecture of digital labor: Converting play into YouTube money. New Media & Society, 18(2), 332–349.CrossRefGoogle Scholar
Prakasam, N., & Huxtable-Thomas, L. (2021). Reddit: Affordances as an enabler for shifting loyalties. Information Systems Frontiers, 23(3), 723–751.CrossRefGoogle Scholar
Putnam, R. D., (2000). Bowling alone: The collapse and revival of American community. Simon Schuster.Google Scholar
Rathnayake, C., & Winter, J. S. (2018). Carrying forward the uses and grats 2.0 agenda: An affordance-driven measure of social media uses and gratifications. Journal of Broadcasting & Electronic Media, 62(3), 371–389.CrossRefGoogle Scholar
Rice, L. L., & Moffett, K. W. (2019). Snapchat and civic engagement among college students. Journal of Information Technology & Politics, 16(2), 87–104.CrossRefGoogle Scholar
Robertson, S. P., Vatrapu, R. K., &Medina, R. (2010). Online video “friends” social networking: Overlapping online public spheres in the 2008 U.S. presidential election. Journal of Information Technology & Politics, 7, 182–201.CrossRefGoogle Scholar
Rojas, H., & Puig-i-Abril, E. (2009). Mobilizers mobilized: Information, expression, mobilization and participation in the digital age. Journal of Computer-Mediated Communication, 14(4), 902–927.CrossRefGoogle Scholar
Rosen, J. (2006). The people formerly known as the audience. Huffington Post. www.huffingtonpost.com/jay-rosen/the-people-formerly-known_1_b_24113.html.Google Scholar
Ruggiero, T. E. (2000). Uses and gratifications theory in the 21st century. Mass Communication & Society, 3(1), 3–37.CrossRefGoogle Scholar
Saldaña, M., McGregor, S. C., & Gil de Zúñiga, H. (2015). Social media as a public space for politics: Cross-national comparison of news consumption and participatory behaviors in the United States and the United Kingdom. International Journal of Communication, 9(1), 3304–3326.Google Scholar
Scheufele, D. A., & Nisbet, M. C. (2002). Being a citizen online: New opportunities and dead ends. International Journal of Press/Politics, 7(3), 55–75.Google Scholar
Scott, C. R. (1998). To reveal or not to reveal: A theoretical model of anonymous communication. Communication Theory, 8(4), 381–407.Google ScholarPubMed
Shah, D. V. (1998). Civic engagement, interpersonal trust, and television use: An individual-level assessment of social capital. Political Psychology, 19, 469–496.CrossRefGoogle Scholar
Shah, D. V. (2016). Conversation is the soul of democracy: Expression effects, communication mediation, and digital media. Communication and the Public, 1(1), 12–18.CrossRefGoogle Scholar
Shah, D. V., Cho, J., Eveland, W. P., & Kwak, N. (2005). Information and expression in a digital age: Modeling internet effects on civic participation. Communication Research, 32, 531–565.CrossRefGoogle Scholar
Shane-Simpson, C., Manago, A., Gaggi, N., & Gillespie-Lynch, K. (2018). Why do college students prefer Facebook, Twitter, or Instagram? Site affordances, tensions between privacy and self-expression, and implications for social capital. Computers in Human Behavior, 86, 276–288.CrossRefGoogle Scholar
Sheldon, P., & Bryant, K. (2016). Instagram: Motives for its use and relationship to narcissism and contextual age. Computers in Human Behavior, 58, 89–97.CrossRefGoogle Scholar
Skoric, M. M., & Zhu, Q. (2016). Social media and offline political participation: Uncovering the paths from digital to physical. International Journal of Public Opinion Research, 28(3), 415–427.CrossRefGoogle Scholar
Skoric, M. M., Zhu, Q., Goh, D., & Pang, N. (2016). Social media and citizen engagement: A meta-analytic review. New Media & Society, 18(9), 1817–1839.CrossRefGoogle Scholar
Slater, M. D. (2004). Operationalizing and analyzing exposure: The foundation of media effects research. Journalism & Mass Communication Quarterly, 81(1), 168–183.CrossRefGoogle Scholar
Song, H., Gil de Zúñiga, H., & Boomgaarden, H. G. (2020). Social media news use and political cynicism: Differential pathways through “news finds me” perception. Mass Communication & Society, 23(1), 47–70.CrossRefGoogle Scholar
Steinberg, A. (2015). Exploring Web 2.0 political engagement: Is new technology reducing the biases of political participation? Electoral Studies, 39, 102–116.CrossRefGoogle Scholar
Stolle, D., & Micheletti, M. (2013) Political consumerism: Global responsibility in action. Cambridge University Press.CrossRefGoogle Scholar
Sundar, S. S. (2008). The MAIN model: A heuristic approach to understanding technology effects on credibility. In Metzger, M. J. & Flanagin, A. J. (Eds.), Digital media, youth, and credibility (pp. 72–100). MIT Press.Google Scholar
Sundar, S. S., & Limperos, A. M. (2013). Uses and grats 2.0: New gratifications for new media. Journal of Broadcasting & Electronic Media, 57(4), 504–525.CrossRefGoogle Scholar
Taber, C. S., Cann, D., & Kucsova, S. (2009). The motivated processing of political arguments. Political Behavior, 31(2), 137–155.CrossRefGoogle Scholar
Tang, G., & Lee, F. L. (2013). Facebook use and political participation: The impact of exposure to shared political information, connections with public political actors, and network structural heterogeneity. Social Science Computer Review, 31(6), 763–773.CrossRefGoogle Scholar
Tewksbury, D., Weaver, A. J., & Maddex, B. D. (2001) Accidentally informed: Incidental news exposure on the World Wide Web. Journalism & Mass Communication Quarterly, 78(3), 533–554.CrossRefGoogle Scholar
Theocharis, Y. (2015). The conceptualization of digitally networked participation. Social Media + Society, 1(2).CrossRefGoogle Scholar
Theocharis, Y., de Moor, J., & van Deth, J. W. (2019). Digitally networked participation and lifestyle politics as new modes of political participation. Policy & Internet.Google Scholar
Theocharis, Y., & van Deth, J. W. (2018a). Political participation in a changing world: Conceptual and empirical dhallenges in the study of citizen engagement. Routledge.Google Scholar
Theocharis, Y., & van Deth, J. W. (2018b). The continuous expansion of citizen participation: A new taxonomy. European Political Science Review, 10(1), 139–163.CrossRefGoogle Scholar
Thorson, K. (2020). Attracting the news: Algorithms, platforms, and reframing incidental exposure. Journalism, 1464884920915352.CrossRefGoogle Scholar
Thorson, K., & Edgerly, S. (2017). Civic engagement through media. In Rössler, P. (Ed.) The international encyclopedia of media effects (pp. 1–12). John Wiley & Sons.Google Scholar
Thorson, K., & Wells, C. (2015). How gatekeeping still matters: Understanding media effects in an era of curated flows. In Vos, T. & Heinderyckx, F. (Eds.), Gatekeeping in transition (pp. 39–58). New York: RoutledgeGoogle Scholar
Thorson, K., & Wells, C. (2016). Curated flows: A framework for mapping media exposure in the digital age. Communication Theory, 26, 309–328.CrossRefGoogle Scholar
Treem, J. W., & Leonardi, P. M. (2013). Social media use in organizations: Exploring the affordances of visibility, editability, persistence, and association. Annals of the International Communication Association, 36(1), 143–189.CrossRefGoogle Scholar
Tufekci, Z., & Wilson, C. (2012). Social media and the decision to participate in political protest: Observations from Tahrir Square. Journal of Communication, 62(2), 363–379.CrossRefGoogle Scholar
Turcotte, J., York, C., Irving, J., Scholl, R. M., & Pingree, R. J. (2015). News recommendations from social media opinion leaders: Effects on media trust and information seeking. Journal of Computer-Mediated Communication, 20(5), 520–535.CrossRefGoogle Scholar
Turner, J. C. (1999). Some current issues in research on social identity and self-categorization theories. Social Identity: Context, Commitment, Content, 3(1), 6–34.Google Scholar
Turner, J. C., & Tajfel, H. (1986). The social identity theory of intergroup behavior. Psychology of Intergroup Relations, 5, 7–24.Google Scholar
Valentino, N.A,. Brader, T., Groenendyk, E. W., et al. (2011) Election night’s alright for fighting: The role of emotions in political participation. Journal of Politics, 73(1), 156–170.CrossRefGoogle Scholar
Valenzuela, S. (2013). Unpacking the use of social media for protest behavior: The roles of information, opinion expression, and activism. American Behavioral Scientist, 57, 920–942.CrossRefGoogle Scholar
Valenzuela, S., Arriagada, A., & Scherman, A. (2012). The social media base of youth protest behavior: The case of Chile. Journal of Communication, 62(2), 299–314.CrossRefGoogle Scholar
Valenzuela, S., Arriagada, A., & Scherman, A. (2014). Facebook, Twitter, and youth engagement: A quasi-experimental study of social media use and protest behavior using propensity score matching. International Journal of Communication, 8, 2046–2070.Google Scholar
Valenzuela, S., Bachmann, I., & Bargsted, M. (2019). The personal is the political? What do WhatsApp users share and how it matters for news knowledge, polarization and participation in Chile. Digital Journalism, 1–21.Google Scholar
Valenzuela, S., Correa, T., & Gil de Zuniga, H. (2018). Ties, likes, and tweets: Using strong and weak ties to explain differences in protest participation across Facebook and Twitter use. Political Communication, 35(1), 117–134.CrossRefGoogle Scholar
Valenzuela, S., Park, N., & Kee, K. F. (2009). Is there social capital in a social network site? Facebook use and college students’ life satisfaction, trust, and participation. Journal of Computer-Mediated Communication, 14(4), 875–901.CrossRefGoogle Scholar
Valenzuela, S., Somma, N., Scherman, A., & Arriagada, A. (2016). Social media in Latin America: Deepening or bridging gaps in protest participation? Online Information Review, 40, 695–711.CrossRefGoogle Scholar
Valeriani, A., & Vaccari, C. (2016) Accidental exposure to politics on social media as online participation equalizer in Germany, Italy, and the United Kingdom. New Media & Society, 18(9), 1857–1874.CrossRefGoogle Scholar
Van Bavel, J. J., & Pereira, A. (2018). The partisan brain: An identity-based model of political belief. Trends in Cognitive Sciences, 22(3), 213–224.CrossRefGoogle Scholar
Van Deth, J. W. (2014). A conceptual map of political participation. Acta Politica, 49(3), 349–367.CrossRefGoogle Scholar
Van Deursen, A. J., & Helsper, E. J. (2015). The third-level digital divide: Who benefits most from being online? In Communication and Information Technologies Annual. Emerald Group Publishing Limited.Google Scholar
Verba, S., & Nie, N. (1972). Participation in America: Social equality and political democracy. Harper & Row.Google Scholar
Verba, S., Schlozman, K. L., & Brady, H. E. (1995). Voice and equality: Civic voluntarism in American politics. Harvard University Press.CrossRefGoogle Scholar
Weeks, B. E., & Holbert, R. L. (2013). Predicting dissemination of news content in social media: A focus on reception, friending, and partisanship. Journalism and Mass Communication Quarterly, 90, 212–232.CrossRefGoogle Scholar
Wellman, B. (2001). Physical place and cyberplace: The rise of personalized networking. International Journal of Urban and Regional Research, 25(2), 227–252.CrossRefGoogle Scholar
Whiting, A., & Williams, D. (2013). Why people use social media: A uses and gratifications approach. Qualitative Market Research: An International Journal, 16, 362–369.CrossRefGoogle Scholar
Wright, S. C., Taylor, D. M., & Moghaddam, F. M. (1990). Responding to membership in a disadvantaged group: From acceptance to collective protest. Journal of Personality and Social Psychology, 58, 994–1003.CrossRefGoogle Scholar
Xenos, M., & Moy, P. (2007). Direct and differential effects of the Internet on political and civic engagement. Journal of Communication, 57(4), 704–718.CrossRefGoogle Scholar
Yardi, S., & Boyd, d. (2010). Dynamic debates: An analysis of group polarization over time on Twitter. Bulletin of Science, Technology & Society, 30, 316–327.CrossRefGoogle Scholar
Yu, T., & Chen, Y. (2020). Live streaming for political campaigns: Persuasive affordances, political mindfulness, and political participation. Association for Information Systems.Google Scholar
Zuckerman, E. (2014). New media, new civics? Policy & Internet, 6(2), 151–168.CrossRefGoogle Scholar
Zukin, C., Keeter, S., Andolina, M., Jenkins, K., & Carpini, M. X. D. (2006). A new engagement? Political participation, civic life, and the changing American citizen. Oxford University Press.CrossRefGoogle Scholar
References
Akhgar, B., Fortune, D., Hayes, R. E., Guerra, B., & Manso, M. (2013). Social media in crisis events: Open networks and collaboration supporting disaster response and recovery. In 2013 IEEE International Conference on Technologies for Homeland Security (HST) (pp. 760–765). IEEE. https://doi.org/10.1109/THS.2013.6699099CrossRefGoogle Scholar
Alam, F., Ofli, F., & Imran, M. (2018). Processing social media images by combining human and machine computing during crises. International Journal of Human–Computer Interaction, 34(4), 311–327. https://doi.org/10.1080/10447318.2018.1427831CrossRefGoogle Scholar
Alam, F., Ofli, F., & Imran, M. (2019). Descriptive and visual summaries of disaster events using artificial intelligence techniques: Case studies of Hurricanes Harvey, Irma, and Maria. Behaviour & Information Technology, 1–31. https://doi.org/10.1080/0144929X.2019.1610908CrossRefGoogle Scholar
Allcott, H., Gentzkow, M., & Yu, C. (2019). Trends in the diffusion of misinformation on social media. Research and Politics, 6(2). https://doi.org/10.1177/2053168019848554CrossRefGoogle Scholar
Allen, C. (2004). Tracing the Evolution of Social Software. www.lifewithalacrity.com/2004/10/tracing_the_evo.htmlGoogle Scholar
American Red Cross. (2012). More Americans Using Mobile Apps in Emergencies. Retrieved May 26, 2014, from www.redcross.org/news/press-release/More-Americans-Using-Mobile-Apps-in-EmergenciesGoogle Scholar
Bergstrand, F., Landgren, J., & Green, V. (2013). Authorities don’t tweet, employees do! In Proceedings of the International Conference on Human–Computer Interaction with Mobile Devices and Services (MobileHCI). ACM. http://dx.doi.org/10.13140/2.1.3099.2644Google Scholar
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3(4–5), 993–1022. https://doi.org/10.1016/b978-0-12-411519-4.00006-9Google Scholar
Burnett, M., Kulesza, T., Oleson, A., Ernst, S., Beckwith, L., Cao, J., … & Grigoreanu, V. (2017). Toward theory-based end-user software engineering. In Paternò, F. & Wulf, V. (Eds.), New perspectives in end-user development (pp. 231–268). Springer International. https://doi.org/10.1007/978-3-319-60291-2_10CrossRefGoogle Scholar
Canadian Red Cross. (2012). Social Media during Emergencies. www.redcross.ca/cmslib/general/pub_social_media_in_emergencies_survey_oct2012_en.pdfGoogle Scholar
Castillo, C. (2016). Big crisis data: Social media in disasters and time-critical situations. Cambridge University Press.CrossRefGoogle Scholar
Chauhan, A., & Hughes, A. L. (2017). Providing online crisis information: An analysis of official sources during the 2014 Carlton Complex wildfire. In Proceedings of the 35th International Conference on Human Factors in Computing Systems (CHI 2017). ACM. https://doi.org/10.1145/3025453.3025627Google Scholar
Chrpa, L., & Thórisson, K. R. (2013). On applicability of automated planning for incident management. In The international Scheduling and Planning Applications woRKshop (pp. 1–7). University of Huddersfield. http://eprints.hud.ac.uk/id/eprint/24490/Google Scholar
Cinelli, M., Quattrociocchi, W., Galeazzi, A., Valensise, C. M., Brugnoli, E., Schmidt, A. L., … & Scala, A. (2020). The COVID-19 Social Media Infodemic, 1–18. http://arxiv.org/abs/2003.05004Google Scholar
Cobb, C., McCarthy, T., Perkins, A., Bharadwaj, A., Comis, J., Do, B., & Starbird, K. (2014). Designing for the deluge: Understanding & supporting the distributed, collaborative work of crisis volunteers. In Proceedings of the Conference on Computer Supported Cooperative Work (CSCW) (pp. 888–899). ACM. https://doi.org/10.1145/2531602.2531712Google Scholar
Delibaši, B., Vuki, M., Jovanovi, M., & Suknovi, M. (2013). White-box or black-box decision tree algorithms: Which to use in education? IEEE Transactions on Education, 56(3), 287–291.CrossRefGoogle Scholar
Denef, S., Bayerl, P. S., & Kaptein, N. (2013). Social media and the police – tweeting practices of British police forces during the August 2011 riots. In Proceedings of the Conference on Human Factors in Computing Systems (CHI) (pp. 3471–3480). ACM. https://doi.org/10.1145/2470654.2466477Google Scholar
Du, M., Liu, N., & Hu, X. (2020). Techniques for interpretable machine learning. Communications of the ACM, 63(1), 68–77. https://doi.org/10.1145/3359786CrossRefGoogle Scholar
Eismann, K., Posegga, O., & Fischbach, K. (2016). Collective behaviour, social media, and disasters: A systematic literature review. In European Conference on Information Systems (ECIS). AIS Electronic Library (AISeL). https://aisel.aisnet.org/ecis2016_rp/104/Google Scholar
Fahad, A., Alshatri, N., Tari, Z., Alamri, A., Khalil, I., Zomaya, A. Y., … & Bouras, A. (2014). A survey of clustering algorithms for big data: Taxonomy and empirical analysis. IEEE Transactions on Emerging Topics in Computing, 2(3), 267–279. https://doi.org/10.1109/TETC.2014.2330519CrossRefGoogle Scholar
Fathi, R., Thom, D., Koch, S., Ertl, T., & Fiedrich, F. (2020). VOST: A case study in voluntary digital participation for collaborative emergency management. Information Processing and Management, 57(4), 102174. https://doi.org/10.1016/j.ipm.2019.102174CrossRefGoogle Scholar
Flizikowski, A., Hołubowicz, W., Stachowicz, A., Hokkanen, L., & Delavallade, T. (2014). Social media in crisis management – the iSAR + project survey. In Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM) (pp. 707–711). ISCRAM Digital Library. http://idl.iscram.org/files/flizikowski/2014/499_Flizikowski_etal2014.pdfGoogle Scholar
Goolsby, R. (2010). Social media as crisis platform: The future of community maps/crisis maps. ACM Transactions on Intelligent Systems and Technology, 1(1), 1–11. https://doi.org/10.1145/1858948.1858955CrossRefGoogle Scholar
Gründer-Fahrer, S., Schlaf, A., Wiedemann, G., & Heyer, G. (2018). Topics and topical phases in German social media communication during a disaster. Natural Language Engineering, 24. https://doi.org/10.1017/S1351324918000025CrossRefGoogle Scholar
Habdank, M., Rodehutskors, N., & Koch, R. (2017). Relevancy assessment of tweets using supervised learning techniques mining emergency related tweets for automated relevancy classification. In 2017 4th International Conference on Information and Communication Technologies for Disaster Management (ICT-DM). IEEE. https://doi.org/10.1109/ICT-DM.2017.8275670Google Scholar
Hagar, C. (2007). The information needs of farmers and use of ICTs. In Nerlich, B. & Doring, M. (Eds.), From mayhem to meaning: Assessing the social and cultural impact of the 2001 foot and mouth outbreak in the UK. Manchester University Press.Google Scholar
Harrald, J. R., Egan, D. M., & Jefferson, T. (2002). Web enabled disaster and crisis response: What have we learned from September 11th? In Proceedings of the Bled eConference (pp. 69–83). University of Maribor. https://domino.fov.uni-mb.si/proceedings.nsf/proceedings/d3a6817c6cc6c4b5c1256e9f003bb2bd/$file/harrald.pdfGoogle Scholar
Hartwig, K., & Reuter, C. (2019). TrustyTweet: An indicator-based browser-plugin to assist users in dealing with fake news on Twitter. In Proceedings of the International Conference on Wirtschaftsinformatik (WI). Siegen.Google Scholar
Haunschild, J., Kaufhold, M.-A., & Reuter, C. (2020). Sticking with landlines? Citizens’ and police social media use and expectation during emergencies. In Proceedings of the International Conference on Wirtschaftsinformatik (WI). GITO. https://doi.org/10.30844/wi_2020_o2-haunschildGoogle Scholar
Helsloot, I., & Ruitenberg, A. (2004). Citizen response to disasters: A survey of literature and some practical implications. Journal of Contingencies and Crisis Management, 12(3), 98–111. https://doi.org/10.1111/j.0966-0879.2004.00440.xCrossRefGoogle Scholar
Hiltz, S. R., Diaz, P., & Mark, G. (2011). Introduction: Social media and collaborative systems for crisis management. ACM Transactions on Computer–Human Interaction, 18(4), 1–6. https://doi.org/10.1145/2063231.2063232CrossRefGoogle Scholar
Hiltz, S. R., & Plotnick, L. (2013). Dealing with information overload when using social media for emergency management: Emerging solutions. In Comes, T., Fiedrich, F., Fortier, S., Geldermann, J., & Müller, T. (Eds.), Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM) (pp. 823–827). ISCRAM Digital Library. http://idl.iscram.org/files/hiltz/2013/583_Hiltz+Plotnick2013.pdfGoogle Scholar
Hughes, A. L., & Palen, L. (2009). Twitter adoption and use in mass convergence and emergency events. International Journal of Emergency Management, 6(3-4), 248–260. https://doi.org/10.1504/IJEM.2009.031564CrossRefGoogle Scholar
Hughes, A. L., & Palen, L. (2012). The evolving role of the public information officer: An examination of social media in emergency management. Journal of Homeland Security and Emergency Management, 9(1), Article 22. https://doi.org/10.1515/1547-7355.1976CrossRefGoogle Scholar
Hughes, A. L., & Palen, L. (2014). Social media in emergency management: Academic perspective. In Trainor, J. E. & Subbio, T. (Eds.), Critical issues in disaster science and management: A dialogue between scientists and emergency managers. Federal Emergency Management Agency.Google Scholar
Hughes, A. L., St. Denis, L. A., Palen, L., & Anderson, K. M. (2014). Online public communications by police & fire services during the 2012 Hurricane Sandy. In Proceedings of the Conference on Human Factors in Computing Systems (CHI) (pp. 1505–1514). ACM. https://doi.org/https://doi.org/10.1145/2556288.2557227Google Scholar
Hughes, A. L., & Tapia, A. H. (2015). Social media in crisis: When professional responders meet digital volunteers. Journal of Homeland Security and Emergency Management, 12(3), 679–706. https://doi.org/10.1515/jhsem-2014-0080CrossRefGoogle Scholar
Imran, M., Castillo, C., Diaz, F., & Vieweg, S. (2015). Processing social media messages in mass emergency: A survey. ACM computing surveys (Vol. 47). ACM. https://doi.org/10.1145/2771588CrossRefGoogle Scholar
Imran, M., Castillo, C., Diaz, F., & Vieweg, S. (2018). Processing social media messages in mass emergency: Survey summary. In Companion Proceedings of the The Web Conference 2018 (WWW’18) (pp. 507–511). ACM. https://doi.org/10.1145/3184558.3186242Google Scholar
Imran, M., Ofli, F., Caragea, D., & Torralba, A. (2020). Using AI and social media multimodal content for disaster response and management: Opportunities, challenges, and future directions. Information Processing and Management, 57(5), 1–9. https://doi.org/10.1016/j.ipm.2020.102261CrossRefGoogle Scholar
International Association of Chiefs of Police. (2010). 2010 Social Media Survey Results. www.iacpsocialmedia.org/Portals/1/documents/Survey%20Results%20Document.pdfGoogle Scholar
International Association of Chiefs of Police. (2015). 2015 Social Media Survey Results. Retrieved from www.iacpsocialmedia.org/Portals/1/documents/FULL%202015%20Social%20Media%20Survey%20Results.pdfGoogle Scholar
Johansson, F., Brynielsson, J., & Quijano, M. N. (2012). Estimating Citizen Alertness in Crises Using Social Media Monitoring and Analysis. 2012 European Intelligence and Security Informatics Conference, 189–196. https://doi.org/10.1109/EISIC.2012.23CrossRefGoogle Scholar
Kaewkitipong, L., Chen, C., & Ractham, P. (2012). Lessons learned from the use of social media in combating a crisis: A case study of 2011 Thailand flooding disaster. In Proceedings of the International Conference on Information Systems (ICIS) (pp. 1–17). AIS Electronic Library (AISeL). https://aisel.aisnet.org/icis2012/proceedings/ProjectManagement/8/Google Scholar
Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68. https://doi.org/10.1016/j.bushor.2009.09.003CrossRefGoogle Scholar
Kaufhold, M.-A. (2020). Information refinement technologies for crisis informatics: User expectations and design implications for social media and mobile apps in crises. Dissertation (Dr. rer. nat.), Technische Universität Darmstadt.Google Scholar
Kaufhold, M.-A., Bayer, M., & Reuter, C. (2020). Rapid relevance classification of social media posts in disasters and emergencies: A system and evaluation featuring active, incremental and online learning. Information Processing and Management, 57(1), 1–32. https://doi.org/10.1016/j.ipm.2019.102132CrossRefGoogle Scholar
Kaufhold, M.-A., Gizikis, A., Reuter, C., Habdank, M., & Grinko, M. (2019). Avoiding chaotic use of social media before, during, and after emergencies: Design and evaluation of citizens’ guidelines. Journal of Contingencies and Crisis Management, 27(3), 198–213. https://doi.org/10.1111/1468-5973.12249CrossRefGoogle Scholar
Kaufhold, M.-A., & Reuter, C. (2014). Vernetzte Selbsthilfe in Sozialen Medien am Beispiel des Hochwassers 2013 / Linked self-help in social media using the example of the floods 2013 in Germany. I-Com – Zeitschrift Für Interaktive Und Kooperative Medien, 13(1), 20–28. https://doi.org/10.1515/icom.2014.0004Google Scholar
Kaufhold, M.-A., & Reuter, C. (2016). The self-organization of digital volunteers across social media: The case of the 2013 European floods in Germany. Journal of Homeland Security and Emergency Management, 13(1), 137–166. https://doi.org/10.1515/jhsem-2015-0063CrossRefGoogle Scholar
Kaufhold, M.-A., & Reuter, C. (2017). The impact of social media in emergencies: A case study with the fire department of Frankfurt. In Tina, Comes, Bénaben, F., Hanachi, C., & Lauras, M. (Eds.), Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM) (pp. 603–612). ISCRAM. Retrieved from http://idl.iscram.org/files/marc-andrekaufhold/2017/1494_Marc-AndreKaufhold+ChristianReuter2017.pdfGoogle Scholar
Kaufhold, M.-A., & Reuter, C. (2019). Cultural violence and peace in social media. In Reuter, C. (Ed.), Information technology for peace and security – IT applications and infrastructures in conflicts, crises, war, and peace (pp. 361–381). Springer Vieweg. https://doi.org/10.1007/978-3-658-25652-4_17Google Scholar
Kaufhold, M.-A., Rupp, N., Reuter, C., Amelunxen, C., & Cristaldi, M. (2018). 112.SOCIAL: Design and evaluation of a mobile crisis app for bidirectional communication between emergency services and citizens. In Proceedings of the European Conference on Information Systems (ECIS). AIS Electronic Library (AISeL). Retrieved from https://aisel.aisnet.org/ecis2018_rp/81/Google Scholar
Kaufhold, M.-A., Rupp, N., Reuter, C., & Habdank, M. (2020). Mitigating information overload in social media during conflicts and crises: Design and evaluation of a cross-platform alerting system. Behaviour & Information Technology (BIT), 39(3), 319–342.CrossRefGoogle Scholar
Keim, D., Andrienko, G., Fekete, J., Carsten, G., & Melan, G. (2008). Visual analytics: Definition, process and challenges. In Kerren, A., Stasko, J. T., Fekete, JD., North, C. (Eds.), Information visualization – Human-centered issues and perspectives (pp. 154–175). Springer. https://doi.org/10.1007/978-3-540-70956-5_7CrossRefGoogle Scholar
Kircher, F. (2014). Ungebundene Helfer im Katastrophenschutz – Die Sicht der Behörden und Organisationen mit Sicherheitsaufgaben. BRANDSchutz – Deutsche Feuerwehr-Zeitung, 593–597.Google Scholar
Koch, M. (2008). CSCW and Enterprise 2.0 – Towards an integrated perspective. In Proceedings of the Bled eConference. AIS Electronic Library (AISeL). https://aisel.aisnet.org/bled2008/15/Google Scholar
Kogan, M., Anderson, J., Palen, L., Anderson, K. M., & Soden, R. (2016). Finding the way to OSM mapping practices: Bounding large crisis datasets for qualitative investigation. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (pp. 2783–2795). ACM. https://doi.org/10.1145/2858036.2858371Google Scholar
Landesberger, T. Von, Kuijper, A., Schreck, T., Kohlhammer, J., Wijk, J. Van, Fekete, J.-D., & Fellner, D. (2011). Visual analysis of large graphs: State-of-the-art and future research challenges. Computer Graphics Forum, 30(6), 1719–1749. https://doi.org/10.1111/j.1467-8659.2011.01898.xCrossRefGoogle Scholar
Latonero, M., & Shklovski, I. (2011). Emergency management, Twitter, and social media evangelism. International Journal of Information Systems for Crisis Response and Management, 3(4), 1–16.CrossRefGoogle Scholar
Ley, B., Ludwig, T., Pipek, V., Randall, D., Reuter, C., & Wiedenhoefer, T. (2014). Information and expertise sharing in inter-organizational crisis management. Computer Supported Cooperative Work: The Journal of Collaborative Computing, 23(4–6), 347–387.CrossRefGoogle Scholar
Ludwig, T., Kotthaus, C., Reuter, C., Dongen, S. Van, Pipek, V., van Dongen, S., & Pipek, V. (2016). Situated crowdsourcing during disasters: Managing the tasks of spontaneous volunteers through public displays. International Journal on Human-Computer Studies. In press.Google Scholar
Mendoza, M., Poblete, B., & Castillo, C. (2010). Twitter under crisis: Can we trust what we RT? In Proceedings of the First Workshop on Social Media Analytics (pp. 71–79). ACM. https://doi.org/10.1145/1964858.1964869Google Scholar
Miller, G. A. (1956). The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychological Review. American Psychological Association. https://doi.org/10.1037/h0043158CrossRefGoogle Scholar
Mirbabaie, M., Bunker, D., Stieglitz, S., & Deubel, A. (2020). Who sets the tone? Determining the impact of convergence behaviour archetypes in social media crisis communication. Information Systems Frontiers, 22(2), 339–351. https://doi.org/10.1007/s10796-019-09917-xCrossRefGoogle Scholar
Mirbabaie, M., Bunker, D., Stieglitz, S., Marx, J., & Ehnis, C. (2020). Social media in times of crisis: Learning from Hurricane Harvey for the coronavirus disease 2019 pandemic response. Journal of Information Technology, 35(3), 195–213. https://doi.org/10.1177/0268396220929258CrossRefGoogle Scholar
Moi, M., Friberg, T., Marterer, R., Reuter, C., Ludwig, T., Markham, D., … & Muddiman, A. (2015). Strategy for processing and analyzing social media data streams in emergencies. In Proceedings of the International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) (pp. 1–7). IEEE. https://doi.org/10.1109/ICT-DM.2015.7402055Google Scholar
O’Reilly, T. (2007). What is Web 2.0? Design patterns and business models for the next generation of software. International Journal of Digital Economics, 65(March), 17–37.Google Scholar
Oliveira, M., & Gama, J. (2012). An overview of social network analysis. WIREs Data Mining and Knowledge Discovery, 2, 99–115. https://doi.org/10.1002/widm.1048CrossRefGoogle Scholar
Olteanu, A., Vieweg, S., & Castillo, C. (2015). What to expect when the unexpected happens: Social media communications across crises. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (pp. 994–1009). ACM. https://doi.org/10.1145/2675133.2675242Google Scholar
Onorati, T., Díaz, P., & Carrion, B. (2018). From social networks to emergency operation centers: A semantic visualization approach. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2018.01.052CrossRefGoogle Scholar
Palen, L. (2020). Crisis Informatics: Human-Centered Research on Tech & Crises – A Guided Bibliography Developed by Crisis Informatics Researchers. Retrieved from https://docs.google.com/document/d/1g6I8Br3vTC04iXVHFTee6arKVld89x9bGvSEeN_NaPU/editGoogle Scholar
Palen, L., & Anderson, K. M. (2016). Crisis informatics: New data for extraordinary times. Science, 353(6296), 224–225. https://doi.org/10.1126/science.aag2579CrossRefGoogle ScholarPubMed
Palen, L., & Hughes, A. L. (2018). Social media in disaster communication. In Rodríguez, H., Donner, W., & Trainor, J. E. (Eds.), Handbook of disaster research (pp. 497–518). Springer International Publishing. https://doi.org/10.1007/978-3-319-63254-4_24CrossRefGoogle Scholar
Palen, L., & Liu, S. B. (2007). Citizen communications in crisis: Anticipating a future of ICT-supported public participation. In Proceedings of the Conference on Human Factors in Computing Systems (CHI) (pp. 727–736). ACM. https://doi.org/10.1145/1240624.1240736Google Scholar
Palen, L., Vieweg, S., Liu, S. B., & Hughes, A. L. (2009). Crisis in a networked world: Features of computer-mediated communication in the April 16, 2007, Virginia Tech Event. Social Science Computer Review, 27(4), 467–480. https://doi.org/10.1177/0894439309332302CrossRefGoogle Scholar
Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1–2), 1–135.CrossRefGoogle Scholar
Perng, S.-Y., Büscher, M., Wood, L., Halvorsrud, R., Stiso, M., Ramirez, L., & Al-Akkad, A. (2012). Peripheral response: Microblogging during the 22/7/2011 Norway attacks. In Rothkrantz, L., Ristvej, J., & Franco, Z. (Eds.), Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM) (pp. 1–11). ISCRAM Digital Library. http://idl.iscram.org/files/perng/2012/187_Perng_etal2012.pdfGoogle Scholar
Pipek, V., Liu, S. B., & Kerne, A. (2014). Special issue: Crisis informatics and collaboration. Computer Supported Cooperative Work, 23(4–6).CrossRefGoogle Scholar
Pipek, V., Reuter, C., Ley, B., Ludwig, T., & Wiedenhoefer, T. (2013). Sicherheitsarena – Ein Ansatz zur Verbesserung des Krisenmanagements durch Kooperation und Vernetzung. Crisis Prevention – Fachmagazin Für Innere Sicherheit, Bevölkerungsschutz Und Katastrophenhilfe, 3(1), 58–59.Google Scholar
Plotnick, L., & Hiltz, S. R. (2016). Barriers to use of social media by emergency managers. Journal of Homeland Security and Emergency Management, 13(2), 247–277. https://doi.org/10.1515/jhsem-2015-0068CrossRefGoogle Scholar
Plotnick, L., Hiltz, S. R., Kushma, J. A., & Tapia, A. (2015). Red tape: Attitudes and issues related to use of social media by U.S. county-level emergency managers. In Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM). ISCRAM Digital Library. http://idl.iscram.org/files/lindaplotnick/2015/1225_LindaPlotnick_etal2015.pdfGoogle Scholar
Pohl, D. (2013). Social Media Analysis for Crisis Management: A Brief Survey. Retrieved May 25, 2014, from http://stcsn.ieee.net/e-letter/vol-2-no-1/social-media-analysis-for-crisis-management-a-brief-surveyGoogle Scholar
Pohl, D., Bouchachia, A., & Hellwagner, H. (2015). Social media for crisis management: Clustering approaches for sub-event detection. Multimedia Tools and Applications, 74(11), 3901–3932. https://doi.org/10.1007/s11042-013-1804-2CrossRefGoogle Scholar
Purohit, H., Hampton, A., Bhatt, S., Shalin, V. L., Sheth, A. P., & Flach, J. M. (2014). Identifying seekers and suppliers in social media communities to support crisis coordination. Computer Supported Cooperative Work: The Journal of Collaborative Computing, 23(4–6), 513–545.CrossRefGoogle Scholar
Qu, Y., Huang, C., Zhang, P., & Zhang, J. (2011). Microblogging after a major disaster in China: A case study of the 2010 Yushu earthquake. In Proceedings of the Conference on Computer Supported Cooperative Work (CSCW) (pp. 25–34). ACM. https://doi.org/10.1145/1958824.1958830Google Scholar
Qu, Y., Wu, P. F., & Wang, X. (2009). Online community response to major disaster: A study of Tianya Forum in the 2008 Sichuan earthquake. In Proceedings of the Hawaii International Conference on System Sciences (HICSS). IEEE. https://doi.org/10.1109/HICSS.2009.330Google Scholar
Quarantelli, E. L. (1984). Emergent citizen groups in disaster preparedness and recovery activities. Final project report. University of Delaware Press.Google Scholar
Quarantelli, E. L. (1995). Emergent behaviors and groups in the crisis time of disasters. University of Delaware, Disaster Research Center.Google Scholar
Quarantelli, E. L., & Dynes, R. R. (1977). Response to social crisis and disaster. Annual Review of Sociology, 3(1), 23–49. https://doi.org/10.1146/annurev.so.03.080177.000323CrossRefGoogle Scholar
Rao, R., Plotnick, L., & Hiltz, S. R. (2017). Supporting the use of social media by emergency managers: Software tools to overcome information overload. In Proceedings of the 50th Hawaii International Conference on System Sciences (HICSS). AIS Digital Library (AISel). https://aisel.aisnet.org/hicss-50/cl/crisis_and_disaster_management/9/Google Scholar
Reuter, C. (2014). Emergent collaboration infrastructures: Technology design for inter-organizational crisis management. PhD Thesis. Siegen, Germany.Google Scholar
Reuter, C., Amelunxen, C., & Moi, M. (2016). Semi-automatic alerts and notifications for emergency services based on cross-platform social media data – Evaluation of a prototype. In Mayr, H. C. & Pinzger, M. (Eds.), Informatik 2016: von Menschen für Menschen. GI-Edition-Lecture Notes in Informatics (LNI).Google Scholar
Reuter, C., Backfried, G., Kaufhold, M.-A., & Spahr, F. (2018). ISCRAM turns 15: A trend analysis of social media papers 2004–2017. In Boersma, K. & Tomaszewski, B. (Eds.), Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM). ISCRAM Digital Library. Retrieved from http://idl.iscram.org/files/christianreuter/2018/2122_ChristianReuter_etal2018.pdfGoogle Scholar
Reuter, C., Heger, O., & Pipek, V. (2013). Combining real and virtual volunteers through social media. In Comes, T., Fiedrich, F., Fortier, S., Geldermann, J., & Müller, T. (Eds.), Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM) (pp. 780–790). ISCRAM Digital Library. http://idl.iscram.org/files/reuter/2013/874_Reuter_etal2013.pdfGoogle Scholar
Reuter, C., Hughes, A. L., & Kaufhold, M.-A. (2018). Social media in crisis management: An evaluation and analysis of crisis informatics research. International Journal on Human–Computer Interaction, 34(4), 280–294. https://doi.org/10.1080/10447318.2018.1427832CrossRefGoogle Scholar
Reuter, C., & Kaufhold, M.-A. (2018). Fifteen years of social media in emergencies: A retrospective review and future directions for crisis informatics. Journal of Contingencies and Crisis Management, 26(1), 41–57. https://doi.org/10.1111/1468-5973.12196CrossRefGoogle Scholar
Reuter, C., Kaufhold, M. A., Schmid, S., Spielhofer, T., & Hahne, A. S. (2019). The impact of risk cultures: Citizens’ perception of social media use in emergencies across Europe. Technological Forecasting and Social Change, 148(119724). https://doi.org/10.1016/j.techfore.2019.119724CrossRefGoogle Scholar
Reuter, C., Kaufhold, M. A., Spahr, F., Spielhofer, T., & Hahne, A. S. (2020). Emergency service staff and social media – A comparative empirical study of the attitude by emergency services staff in Europe in 2014 and 2017. International Journal of Disaster Risk Reduction, 46(101516). https://doi.org/10.1016/j.ijdrr.2020.101516CrossRefGoogle Scholar
Reuter, C., Kaufhold, M.-A., Spielhofer, T., & Hahne, A. S. (2017). Social media in emergencies: A representative study on citizens’ perception in Germany. Proceedings of the ACM: Human–Computer Interaction (PACM): Computer-Supported Cooperative Work and Social Computing, 1(2), 1–19. https://doi.org/10.1145/3134725Google Scholar
Reuter, C., Ludwig, T., Kaufhold, M.-A., & Pipek, V. (2015). XHELP: Design of a cross-platform social-media application to support volunteer moderators in disasters. In Proceedings of the Conference on Human Factors in Computing Systems (CHI) (pp. 4093–4102). ACM. https://doi.org/10.1145/2702123.2702171Google Scholar
Reuter, C., Ludwig, T., Kaufhold, M.-A., & Spielhofer, T. (2016). Emergency services attitudes towards social media: A quantitative and qualitative survey across Europe. International Journal on Human-Computer Studies, 95, 96–111. https://doi.org/10.1016/j.ijhcs.2016.03.005CrossRefGoogle Scholar
Reuter, C., Marx, A., & Pipek, V. (2011). Social software as an infrastructure for crisis management – A case study about current practice and potential usage. In Santos, M. A., Sousa, L., & Portela, E. (Eds.), Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM). ISCRAM Digital Library. http://idl.iscram.org/files/reuter/2011/876_Reuter_etal2011.pdfGoogle Scholar
Reuter, C., Marx, A., & Pipek, V. (2012). Crisis management 2.0: Towards a systematization of social software use in crisis situations. International Journal of Information Systems for Crisis Response and Management, 4(1), 1–16.CrossRefGoogle Scholar
Reuter, C., Mentler, T., & Geisler, S. (2015). Special issue on human computer interaction in critical systems I: Citizen and volunteers. International Journal of Information Systems for Crisis Response and Management, 7(2), 1–80.Google Scholar
Reuter, C., & Scholl, S. (2014). Technical limitations for designing applications for social media. In Koch, M., Butz, A., & Schlichter, J. (Eds.), Mensch & Computer: Workshopband (pp. 131–140). Oldenbourg-Verlag.Google Scholar
Reuter, C., & Spielhofer, T. (2017). Towards social resilience: A quantitative and qualitative survey on citizens’ perception of social media in emergencies in Europe. Journal Technological Forecasting and Social Change, 121, 168–180.CrossRefGoogle Scholar
Reuter, C., Stieglitz, S., & Imran, M. (2020). Social media in conflicts and crises. Behaviour and Information Technology, 39(3), 241–251. https://doi.org/10.1080/0144929X.2019.1629025CrossRefGoogle Scholar
Ritter, A., Clark, S., Mausam, & O. E. (2011). Named entity recognition in tweets: An experimental study. In Merlo, P., Barzilay, R., & Johnson, M. (Eds.), Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) (pp. 1524–1534). Association for Computational Linguistics.Google Scholar
Romero, C., Olmo, J. L., & Ventura, S. (2013). A meta-learning approach for recommending a subset of white-box classification algorithms for Moodle datasets. In Proceedings of the International Conference on Educational Data Mining (EDM) (pp. 268–271). International Educational Data Mining Society. https://educationaldatamining.org/EDM2013/proceedings/paper_3.pdfGoogle Scholar
Rudra, K., Ganguly, N., Goyal, P., & Ghosh, S. (2018). Extracting and summarizing situational information from the Twitter social media during disasters. ACM Transactions on the Web, 12(3), 1–35. https://doi.org/10.1145/3178541CrossRefGoogle Scholar
Rudra, K., Ghosh, S., Ganguly, N., Goyal, P., & Ghosh, S. (2015). Extracting situational information from microblogs during disaster events: A classification-summarization approach. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management (pp. 583–592). ACM. https://doi.org/10.1145/2806416.2806485CrossRefGoogle Scholar
Sakaki, T., Okazaki, M., & Matsuo, Y. (2010). Earthquake shakes Twitter users: real-time event detection by social sensors. In WWW’10: Proceedings of the 19th International Conference on World Wide Web (851). https://doi.org/10.1145/1772690.1772777CrossRefGoogle Scholar
San, Y., Wardell, C. III, & Thorkildsen, Z. (2013). Social Media in the Emergency Management Field: 2012 Survey Results. Retrieved from www.cna.org/sites/default/files/research/SocialMedia_EmergencyManagement.pdfGoogle Scholar
Shneiderman, B. (1996). The eyes have it: A task by data type taxonomy for information visualizations. In Proceedings 1996 IEEE Symposium on Visual Languages (pp. 1–8). IEEE. https://doi.org/10.1109/VL.1996.545307Google Scholar
St. Denis, L. A., Hughes, A. L., & Palen, L. (2012). Trial by fire: The deployment of trusted digital volunteers in the 2011 Shadow Lake Fire. In Rothkrantz, L., Ristvej, J., & Franco, Z. (Eds.), Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM) (pp. 1–10). ISCRAM.Google Scholar
Stallings, R. A., & Quarantelli, E. L. (1985). Emergent citizen groups and emergency management. Public Administration Review, 45(Special Issue), 93–100. https://doi.org/10.2307/3135003CrossRefGoogle Scholar
Starbird, K., Arif, A., & Wilson, T. (2019). Disinformation as collaborative work: Surfacing the participatory nature of strategic information operations. Proceedings of the ACM on Human–Computer Interaction (CSCW), 3, 1–26. https://doi.org/10.1145/3359229CrossRefGoogle Scholar
Starbird, K., & Palen, L. (2011). Voluntweeters: Self-organizing by digital volunteers in times of crisis. In Proceedings of the Conference on Human Factors in Computing Systems (CHI) (pp. 1071–1080). ACM. https://doi.org/10.1145/1978942.1979102Google Scholar
Starbird, K., & Palen, L. (2012). (How) will the revolution be retweeted? Information diffusion and the 2011 Egyptian uprising. In Proceedings of the Conference on Computer Supported Cooperative Work (CSCW) (pp. 7–16). ACM. https://doi.org/10.1145/2145204.2145212Google Scholar
Starbird, K., Palen, L., Hughes, A. L., & Vieweg, S. (2010). Chatter on the red: What hazards threat reveals about the social life of microblogged information. In Proceedings of the Conference on Computer Supported Cooperative Work (CSCW) (pp. 241–250). ACM. https://doi.org/10.1145/1718918.1718965Google Scholar
Statista. (2020). Most popular social networks worldwide as of July 2020, ranked by number of active users. Retrieved August 25, 2020, from www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users/Google Scholar
Stieglitz, S., Dang-Xuan, L., Bruns, A., & Neuberger, C. (2014). Social media analytics: An interdisciplinary approach and its implications for information systems. Business and Information Systems Engineering, 6(2), 89–96. https://doi.org/10.1007/s12599-014-0315-7CrossRefGoogle Scholar
Stieglitz, S., Mirbabaie, M., Fromm, J., & Melzer, S. (2018). The adoption of social media analytics for crisis management – Challenges and opportunities. In Proceedings of the 26th European Conference on Information Systems (ECIS). AIS Electronic Library (AISeL). https://aisel.aisnet.org/ecis2018_rp/4/Google Scholar
Stieglitz, S., Mirbabaie, M., Ross, B., & Neuberger, C. (2018). Social media analytics – Challenges in topic discovery, data collection, and data preparation. International Journal of Information Management, 39, 156–168. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2017.12.002CrossRefGoogle Scholar
Sutton, J. (2010). Twittering Tennessee: Distributed networks and collaboration following a technological disaster. In French, S., Tomaszewski, B., & Zobel, C. (Eds.), Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM). ISCRAM Digital Library. http://idl.iscram.org/files/sutton/2010/987_Sutton2010.pdfGoogle Scholar
Valecha, R., Oh, O., & Rao, R. (2013). An exploration of collaboration over time in collective crisis response during the Haiti 2010 earthquake. In Baskerville, R. & Chau, M. (Eds.), Proceedings of the International Conference on Information Systems (ICIS) (pp. 1–10). AIS Electronic Library (AISeL). Retrieved from https://aisel.aisnet.org/icis2013/proceedings/ResearchInProgress/96/Google Scholar
van Gorp, A. F. (2014). Integration of volunteer and technical communities into the humanitarian aid sector: Barriers to collaboration. In Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM) (pp. 620–629). ISCRAM Digital Library. http://idl.iscram.org/files/vangorp/2014/1042_VanGorp2014.pdfGoogle Scholar
Vieweg, S., Hughes, A. L., Starbird, K., & Palen, L. (2010). Microblogging during two natural hazards events: What Twitter may contribute to situational awareness. In Proceedings of the Conference on Human Factors in Computing Systems (CHI) (pp. 1079–1088). ACM. https://doi.org/10.1145/1753326.1753486Google Scholar
Viviani, M., & Pasi, G. (2017). Credibility in social media: Opinions, news, and health information – A survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7(5), e1209--n/a. https://doi.org/10.1002/widm.1209Google Scholar
White, J. I., Palen, L., & Anderson, K. M. (2014). Digital mobilization in disaster response: The work & self – organization of on-line pet advocates in response to Hurricane Sandy. In Fussell, S. R., Lutters, W. G., Morris, M. R., & Reddy, M. (Eds.), Proceedings of the Conference on Computer Supported Cooperative Work (CSCW) (pp. 866–876). ACM. https://doi.org/10.1145/2531602.2531633Google Scholar
White, C., Plotnick, L., Kushma, J., Hiltz, S. R., & Turoff, M. (2009). An online social network for emergency management. International Journal of Emergency Management, 6(3/4), 369–382.CrossRefGoogle Scholar
Wilensky, H. (2014). Twitter as a navigator for stranded commuters during the Great East Japan earthquake. In Proceedings of the International Conference on Information Systems for Crisis Response and Management (ISCRAM) (pp. 695–704). ISCRAM Digital Library. http://idl.iscram.org/files/wilensky/2014/1091_Wilensky2014.pdfGoogle Scholar
Wukich, C. (2015). Social media use in emergency management. Journal of Emergency Management, 13(4), 281–294. https://doi.org/10.5055/jem.2015.0242CrossRefGoogle ScholarPubMed
Zade, H., Shah, K., Rangarajan, V., Kshirsagar, P., Imran, M., & Starbird, K. (2018). From situational awareness to actionability: Towards improving the utility of social media data for crisis response. In Proceedings of the ACM on Human-Computer Interaction. ACM. https://doi.org/10.1145/3274464Google Scholar
References
Buss, D. M. (1989). Sex differences in human mate preferences: Evolutionary hypotheses tested in 37 cultures. Behavioral and Brain Sciences, 12(1), 1–14. https://doi.org/10.1017/S0140525X00023992CrossRefGoogle Scholar
Eagly, A. H., & Wood, W. (1999). The origins of sex differences in human behavior: Evolved dispositions versus social roles. American Psychologist, 54(6), 408–423. https://doi.org/10.1037/0003–066X.54.6.408CrossRefGoogle Scholar
Eastwick, P. W., & Finkel, E. J. (2008). Sex differences in mate preferences revisited: Do people know what they initially desire in a romantic partner? Journal of Personality and Social Psychology, 94(2), 245–264. https://doi.org/10.1037/0022–3514.94.2.245CrossRefGoogle Scholar
Eastwick, P. W., Finkel, E. J., & Eagly, A. H. (2011). When and why do ideal partner preferences affect the process of initiating and maintaining romantic relationships? Journal of Personality and Social Psychology, 101(5), 1012–1032. https://doi.org/10.1037/a0024062CrossRefGoogle ScholarPubMed
Eastwick, P. W., Keneski, E., Morgan, T. A., McDonald, M. A., & Huang, S. A. (2018). What do short-term and long-term relationships look like? Building the relationship coordination and strategic timing (ReCAST) model. Journal of Experimental Psychology: General, 147(5), 747–781. https://doi.org/10.1037/xge0000428CrossRefGoogle ScholarPubMed
Ellison, N. B., Hancock, J. T., & Toma, C. L. (2012). Profile as promise: A framework for conceptualizing veracity in online dating self-presentations. New Media & Society, 14(1), 45–62. https://doi.org/10.1177/1461444811410395CrossRefGoogle Scholar
Ellison, N., Heino, R., & Gibbs, J. (2006). Managing impressions online: Self-presentation processes in the online dating environment. Journal of Computer-Mediated Communication, 11(2), 415–441. https://doi.org/10.1111/j.1083-6101.2006.00020.xCrossRefGoogle Scholar
Finkel, E. J., & Eastwick, P. W. (2009). Arbitrary social norms influence sex differences in romantic selectivity. Psychological Science, 20(10), 1290–1295. https://doi.org/10.1111/j.1467-9280.2009.02439.xCrossRefGoogle ScholarPubMed
Finkel, E. J., Eastwick, P. W., Karney, B. R., Reis, H. T., & Sprecher, S. (2012). Online dating: A critical analysis from the perspective of psychological science. Psychological Science in the Public Interest, 13(1), 3–66. https://doi.org/10.1177/1529100612436522CrossRefGoogle ScholarPubMed
Fiore, A. T., & Donath, J. S. (2004). Online personals: An overview. CHI’04 Extended Abstracts on Human Factors in Computing Systems, 1395–1398. https://doi.org/10.1145/985921.986073CrossRefGoogle Scholar
Fiore, A. T., Taylor, L. S., Zhong, X., Mendelsohn, G. A., & Cheshire, C. (2010). Who’s Right and Who Writes: People, Profiles, Contacts, and Replies in Online Dating. 2010 43rd Hawaii International Conference on System Sciences, 1–10. https://doi.org/10.1109/HICSS.2010.444CrossRefGoogle Scholar
Gibbs, J. L., Ellison, N. B., & Heino, R. D. (2006). Self-presentation in online personals: The role of anticipated future interaction, self-disclosure, and perceived success in internet dating. Communication Research, 33(2), 152–177. https://doi.org/10.1177/0093650205285368CrossRefGoogle Scholar
Hancock, J. T., & Toma, C. L. (2009). Putting your best face forward: The accuracy of online dating photographs. Journal of Communication, 59(2), 367–386. https://doi.org/10.1111/j.1460-2466.2009.01420.xCrossRefGoogle Scholar
Hancock, J. T., Toma, C., & Ellison, N. (2007). The truth about lying in online dating profiles. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 449–452). ACM. https://doi.org/10.1145/1240624.1240697CrossRefGoogle Scholar
Hill, R. (1945). Campus values in mate selection. Journal of Home Economics, 37(554), 269.Google Scholar
Joel, S., & Eastwick, P. W. (2018). Intervening earlier: An upstream approach to improving relationship quality. Policy Insights from the Behavioral and Brain Sciences, 5(1), 25–32. https://doi.org/10.1177/2372732217745099CrossRefGoogle Scholar
Markowitz, D. M., & Hancock, J. T. (2018). Deception in mobile dating conversations. Journal of Communication, 68(3), 547–569. https://doi.org/10.1093/joc/jqy019CrossRefGoogle Scholar
Ramirez, A. Jr, & Zhang, S. (2007). When online meets offline: The effect of modality switching on relational communication. Communication Monographs, 74(3), 287–310. https://doi.org/10.1080/03637750701543493CrossRefGoogle Scholar
Reis, H. T., & Shaver, P. (1988). Intimacy as an interpersonal process. In Handbook of personal relationships: Theory, research and interventions (pp. 367–389). John Wiley & Sons.Google Scholar
Rosenfeld, M. J., Thomas, R. J., & Hausen, S. (2019). Disintermediating your friends: How online dating in the United States displaces other ways of meeting. Proceedings of the National Academy of Sciences, 116(36), 17753–17758. https://doi.org/10.1073/pnas.1908630116CrossRefGoogle ScholarPubMed
Rubin, Z. (1975). Disclosing oneself to a stranger: Reciprocity and its limits. Journal of Experimental Social Psychology, 11(3), 233–260. https://doi.org/10.1016/S0022-1031(75)80025-4CrossRefGoogle Scholar
Sharabi, L. L. (2020). Online dating profiles, first-date interactions, and the enhancement of communication satisfaction and desires for future interaction. Communication Monographs, 1–23. https://doi.org/10.1080/03637751.2020.1766094CrossRefGoogle Scholar
Sharabi, L. L., & Caughlin, J. P. (2017). What predicts first date success? A longitudinal study of modality switching in online dating. Personal Relationships, 24(2), 370–391. https://doi.org/10.1111/pere.12188CrossRefGoogle Scholar
Sharabi, L. L., & Dykstra-DeVette, T. A. (2019). From first email to first date: Strategies for initiating relationships in online dating. Journal of Social and Personal Relationships, 36(11–12), 3389–3407. https://doi.org/10.1177/0265407518822780CrossRefGoogle Scholar
Simmons, M., & Lee, J. S. (2020). Catfishing: A look into online dating and impersonation. In Meiselwitz, G. (Ed.), Social computing and social media. Design, ethics, user behavior, and social network analysis (pp. 349–358). Springer International Publishing. https://doi.org/10.1007/978-3-030-49570-1_24CrossRefGoogle Scholar
Sorell, T., & Whitty, M. (2019). Online romance scams and victimhood. Security Journal, 32(3), 342–361. https://doi.org/10.1057/s41284-019-00166-wCrossRefGoogle Scholar
Taylor, L., Fiore, A. T., Mendelsohn, G. A., & Cheshire, C. (2011). “Out of my league”: A real-world test of the matching hypothesis. Personality and Social Psychology Bulletin, 37(7), 942–954. https://doi.org/10.1177/0146167211409947CrossRefGoogle Scholar
Tidwell, L. C., & Walther, J. B. (2002). Computer-mediated communication effects on disclosure, impressions, and interpersonal evaluations: Getting to know one another a bit at a time. Human Communication Research, 28(3), 317–348. https://doi.org/10.1111/j.1468-2958.2002.tb00811.xCrossRefGoogle Scholar
Timmermans, E., & Courtois, C. (2018). From swiping to casual sex and/or committed relationships: Exploring the experiences of Tinder users. The Information Society, 34(2), 59–70. https://doi.org/10.1080/01972243.2017.1414093CrossRefGoogle Scholar
Timmermans, E., & De Caluwé, E. (2017a). Development and validation of the Tinder Motives Scale (TMS). Computers in Human Behavior, 70, 341–350. https://doi.org/10.1016/j.chb.2017.01.028CrossRefGoogle Scholar
Timmermans, E., & De Caluwé, E. (2017b). To Tinder or not to Tinder, that’s the question: An individual differences perspective to Tinder use and motives. Personality and Individual Differences, 110, 74–79. https://doi.org/10.1016/j.paid.2017.01.026CrossRefGoogle Scholar
Toma, C. L., & Hancock, J. T. (2010). Looks and lies: The role of physical attractiveness in online dating self-presentation and deception. Communication Research, 37(3), 335–351. https://doi.org/10.1177/0093650209356437CrossRefGoogle Scholar
Toma, C. L., & Hancock, J. T. (2012). What lies beneath: The linguistic traces of deception in online dating profiles. Journal of Communication, 62(1), 78–97. https://doi.org/10.1111/j.1460-2466.2011.01619.xCrossRefGoogle Scholar
Tong, S. T., Corriero, E. F., Matheny, R. G., & Hancock, J. T. (2018). Online daters’ willingness to use recommender technology for mate selection decisions. In IntRS@ RecSys (pp. 45–52).Google Scholar
Tong, S. T., Corriero, E. F., Wibowo, K. A., Makki, T. W., & Slatcher, R. B. (2020). Self-presentation and impressions of personality through text-based online dating profiles: A lens model analysis. New Media & Society, 22(5), 875–895. https://doi.org/10.1177/1461444819872678CrossRefGoogle Scholar
Tong, S. T., Hancock, J. T., & Slatcher, R. B. (2016a). Online dating system design and relational decision making: Choice, algorithms, and control. Personal Relationships, 23(4), 645–662. https://doi.org/10.1111/pere.12158CrossRefGoogle Scholar
Tong, S. T., Hancock, J. T., & Slatcher, R. B. (2016b). The influence of technology on romantic relationships: Understanding online dating. In Meiselwitz, G. (Ed.), Social computing and social media (Vol. 9742, pp. 162–173). Springer International Publishing. https://doi.org/10.1007/978-3-319-39910-2_16CrossRefGoogle Scholar
Tong, S. T., & Walther, J. (2011). Relational maintenance and computer-mediated communication. In Wright, K. B. & Webb, L. M. (Eds.), Computer-mediated communication in personal relationships (pp. 98-118) Peter Lang Publishing.Google Scholar
Turkle, S. (2012). Alone together: Why we expect more from technology and less from each other (1st edition). Basic Books.Google Scholar
Uecker, J. E., & Regnerus, M. D. (2010). BARE MARKET: Campus sex ratios, romantic relationships, and sexual behavior. The Sociological Quarterly, 51(3), 408–435.CrossRefGoogle ScholarPubMed
Walster, E., Aronson, V., Abrahams, D., & Rottman, L. (1966). Importance of physical attractiveness in dating behavior. Journal of Personality and Social Psychology, 4(5), 508–516. https://doi.org/10.1037/h0021188CrossRefGoogle ScholarPubMed
Walther, J. B. (1996). Computer-mediated communication: Impersonal, interpersonal, and hyperpersonal interaction. Communication Research, 23(1), 3–43. https://doi.org/10.1177/009365096023001001CrossRefGoogle Scholar
Walther, J., & Parks, M. (2002). Cues filtered out, cues filtered in: Computer-mediated communication and relationships. In Knapp, M. L. and Daly, J. A. (Eds.), Handbook of interpersonal communication (3rd edn., pp. 529–563). Sage.Google Scholar
Whitty, M. T. (2008). Revealing the “real” me, searching for the “actual” you: Presentations of self on an internet dating site. Computers in Human Behavior, 24(4), 1707–1723. https://doi.org/10.1016/j.chb.2007.07.002CrossRefGoogle Scholar
Whitty, M. T. (2013). The scammers persuasive techniques model: Development of a stage model to explain the online dating romance scam. The British Journal of Criminology, 53(4), 665–684. https://doi.org/10.1093/bjc/azt009CrossRefGoogle Scholar
Whitty, M. T. (2015). Anatomy of the online dating romance scam. Security Journal, 28(4), 443–455. https://doi.org/10.1057/sj.2012.57CrossRefGoogle Scholar
References
Al-Kandari, A. a., & Dashti, A. (2014). Fatwa and the internet: A study of the influence of Muslim religious scholars on internet diffusion in Saudi Arabia. Prometheus, 32(2), 127–144.CrossRefGoogle Scholar
Astley, J., & Francis, L. J. (2013). Exploring ordinary theology: Everyday Christian believing and the church. Ashgate.Google Scholar
Baesler, E. J., & Chen, Y.-F. (2013). Mapping the landscape of digital petitionary prayer as spiritual/social support in mobile, Facebook, and e-mail. Journal of Media and Religion, 12(1), 1–15.CrossRefGoogle Scholar
Bajan, A. (2015). Paradigms of the religious network society. Stream: Culture/Politics/Technology, 7(1), 9–15. Retrieved from http://journals.sfu.ca/streamCrossRefGoogle Scholar
Bellar, W. (2017). iPray: Understanding the Relationship between Design and Use in Catholic and Islamic Mobile Prayer Applications. Doctoral dissertation. Texas A&M University.Google Scholar
Blondheim, M., & Katz, E. (2016). Religion, communications, and Judaism: The case of digital Chabad. Media, Culture & Society, 38(1), 89–95.CrossRefGoogle Scholar
Bobrowski, P., & Pearce, L. (2011). Baring their souls in online profiles or not? Religious self-disclosure in social media. Journal for the Scientific Study of Religion, 50(4), 744–762.CrossRefGoogle Scholar
Brunn, S. D., & Gilbreath, D. A. (2015). The changing world religion map: Sacred places, identities, practices, and politics. Springer.CrossRefGoogle Scholar
Burroughs, B., & Feller, G. (2015). Religious memetics: Institutional authority in digital/lived religion. Journal of Communication Inquiry, 39(4), 357–377.CrossRefGoogle Scholar
Campbell, H. (2007). Who’s got the power? Religious authority and the Internet. Journal of Computer-Mediated Communication, 12(3), 1043–1062.CrossRefGoogle Scholar
Campbell, H. A. (2012). Digital religion: Understanding religious practice in new media worlds. Routledge.CrossRefGoogle Scholar
Campbell, H. A. (2013). Evangelicals and the Internet. In Evangelical Christians and popular culture: Pop goes the gospel. ABC-CLIO.Google Scholar
Campbell, H. A., & DeLashmutt, M. W. (2014). Studying technology and ecclesiology in online multi-site worship. Journal of Contemporary Religion, 29(2), 267–285.CrossRefGoogle Scholar
Campbell, H. & Rule, F. (2016). The practice of digital religion. In The handbook of social practices and digital life-worlds / Handbuch Soziale Praktiken und Digitale Alltagswelten. Friese, Heidrun, Rebane, Gala, Nolden, Marcus und Schreiter, Miriam (Eds.) (pp. 1–12). Springer Publishing.Google Scholar
Castells, M. (2007). Communication, power and counter-power in the network society. International Journal of Communication, 1(June 2006), 238–266.Google Scholar
Cheong, P. H. (2012). Digital religion, social media, and culture: Perspectives, practices, and futures. Peter Lang.Google Scholar
Cheong, P. H. (2016). The vitality of new media and religion: Communicative perspectives, practices, and authority in spiritual organization. New Media and Society, 1(8), 25–33.Google Scholar
Couldry, N. (2012). Media, society, world: Social theory and digital media practice. Polity.Google Scholar
Drescher, E. (2011). Tweet if you [love] Jesus: Practicing church in the digital reformation. Morehouse.Google Scholar
Echchaibi, N. (2009). Hyper-Islamism? Mediating Islam from the Halal website to the Islamic talk show. Journal of Arab & Muslim Media Research, 1(3), 199–214.CrossRefGoogle Scholar
Fader, Ayala. (2017). Ultra-Orthodox Jewish interiority, the Internet, and the crisis of faith. HAU: Journal of Ethnographic Theory, 7(1), 185–206.CrossRefGoogle Scholar
Farrell, J. (2011). The divine online: Civic organizing, identity building, and internet fluency among different religious groups. Journal of Media and Religion, 10(2), 73–90.CrossRefGoogle Scholar
Frost, J. K., & Youngblood, N. E. (2014). Online religion and religion online: Reform Judaism and web-based communication. Journal of Media and Religion, 13(2), 49–66.CrossRefGoogle Scholar
Han, S. (2016). Technologies of religion: Spheres of the sacred in a post-secular modernity. Routledge.CrossRefGoogle Scholar
Hoffman, J. P. (2013). Declining religious authority? Confidence in the leaders of religious organizations. Review of Religious Research, 55(1), 1–25.CrossRefGoogle Scholar
Hoover, S. M., & Clark, L. S. (2002). Practicing religion in the age of the media: Explorations in media, religion, and culture. Routledge.CrossRefGoogle Scholar
Horsfield, P., & Teusner, P. (2000). A mediated religion: Historical perspectives on Christianity and the Internet. Studies in World Christianity, 13(3), 278–295.CrossRefGoogle Scholar
Hutchings, T. (2014). The dis/embodied church: Worship, new media and the body. In Christianity in the modern world. Routledge.Google Scholar
Hutchings, T. (2017). Creating church online: Ritual, community, and new media. Routledge.CrossRefGoogle Scholar
Justice, D. (2014). When church and cinema combine: Blurring boundaries through media-savvy evangelicalism. Journal of Religion, Media, and Digital Culture, 3(1), 84–119.CrossRefGoogle Scholar
Kalantarib, A., & Khojastea, H. (2009). The media rituals: The relationship between media and religion. Asian Journal of Social Science, 37(2), 284–304.Google Scholar
Kuzma, A., Kuzma, A., & Kuzma, J. (2009). How religion has embraced marketing and the implications for business. Journal of Management and Marketing Research, 2(2), 1–10.Google Scholar
Lynch, G., & Mitchell, J. P. (2012). Religion, media, and culture: A reader. Routledge.CrossRefGoogle Scholar
McConnell, S. (2009). Multi-site churches: Guidance for the movement’s next generation. B&H Books.Google Scholar
Nassar, I. A., Hayajneh, J. A., & Mahmoud, K. H. A. (2013). Relation between social network and Da’wah to Islam: A case study on Jordanian students. International Journal on Islamic Applications in Computer Science and Technology, 1(1), 9–18. Retrieved from www.sign-ific-ance.co.uk/index.php/IJASAT/article/view/487/489.Google Scholar
Rahman, A. A., Hashim, N. H., & Mustafa, H. (2015). Muslims in cyberspace: Exploring factors influencing online religious engagements in Malaysia. Media Asia, 42(1–2), 61–73.CrossRefGoogle Scholar
Redden, G. (2013). Mediating faiths: Religion and socio-cultural change in the twenty-first century. Ashgate Publishing, Ltd.Google Scholar
Richardson, K. B., & Pardun, C. J. (2015). The new scroll digital devices, Bible study and worship. Journal of Media and Religion, 14(1), 16–28.CrossRefGoogle Scholar
Senn, F. C. (1997). Christian liturgy: Catholic and evangelical. Augsburg Fortress Press.Google Scholar
Tsuria, R. (2016). Jewish Q and A online and the regulation of sexuality: Using Foucault to read technology. Social Media + Society, 2(3). Retrieved from https://journals.sagepub.com/doi/abs/10.1177/2056305116662176.CrossRefGoogle Scholar
Ward, P. (2005). Selling worship: How what we sing has changed the church. Paternoster Press.Google Scholar
Wasinski, A., & Szyszka, M. (2013). The forms of participation of the Catholic Church in Poland in the modern media space. Jurnalism Si Comunicare, 8(2), 43–57.Google Scholar
Zsupan-Jerome, D. (2014). Religious education fostering the public voice: Blogging as a pedagogical practice in ministerial education. Religious Education, 1093, 331–345.CrossRefGoogle Scholar
References
Ball, H. A., Arsenault, L., Taylor, A., Maughan, B., Caspi, A., & Moffitt, T. E. (2008). Genetic and environmental influences on victims, bullies and bully-victims in childhood. Journal of Child Psychiatry and Psychiatry, 49, 104–112.CrossRefGoogle ScholarPubMed
Barlett, C., & Coyne, S. M. (2014). A meta-analysis of sex differences in cyber-bullying behavior: The moderating role of age. Aggressive Behavior, 40, 474–488.CrossRefGoogle ScholarPubMed
Barlett, C., Simmers, M. M., & Seyfert, L. W. (2021). Advances in the cyberbullying literature: Theory-based interventions. In Schiamberg, L. B. & Wright, M. F. (Eds.), Child and adolescent exposure to online risks: An ecological perspective (pp. 351–377). Elsevier/Academic Press.CrossRefGoogle Scholar
Bauman, S., Underwood, M. K., & Card, N. (2013). Definitions: Another perspective and a proposal for beginning with cyberaggression. In Bauman, S., Walker, J, & Cross, D. (Eds.), Principles of cyberbullying research: Definition, methods, and measures (pp. 87–93). Routledge.Google Scholar
Berne, S., Frisén, A., Schultze-Krumbholz, A., Scheithauer, H., Naruskov, K., Luik, P., Katzer, C., Erentaite, R., & Zukauskiene, R. (2013). Cyberbullying assessment instruments: A systematic review. Aggression and Violent Behavior, 18, 320–334.CrossRefGoogle Scholar
Boulton, M. J., Boulton, L., Camerone, E., Down, J., Hughes, J., Kirkbride, C., Kirkham, R., Macaulay, P., & Sanders, J. (2016). Enhancing primary school children’s knowledge of online safety and risks with the CATZ cooperative cross-age teaching intervention: Results from a pilot study. Cyberpsychology, Behavior, and Social Networking, 19, 609–614.CrossRefGoogle ScholarPubMed
Brochado, S., Soares, S., & Fraga, S. (2017). A scoping review on studies of cyberbullying prevalence among adolescents. Trauma, Violence, & Abuse, 18(5), 523–531.CrossRefGoogle ScholarPubMed
Calvete, E., Orue, I., Estévez, A., Villardón, L., & Padilla, P. (2010). Cyberbullying in adolescents: Modalities and aggressors’ profile. Computers in Human Behavior, 26, 1128–1135.CrossRefGoogle Scholar
Campbell, M. (2019). Specific interventions against cyberbullying. In Smith, P. K. (Ed.), Making an impact on school bullying: Interventions and recommendations (pp. 176–201). Routledge.CrossRefGoogle Scholar
Campbell, M., & Bauman, S., S. (Eds.) (2018). Reducing cyberbullying in schools: International evidenced-based best practices. Elsevier.Google Scholar
Cassidy, W., Faucher, C., & Jackson, M. (Eds.) (2019). Cyberbullying at university in international contexts. Routledge.Google Scholar
Chai, L., Xue, J., & Han, Z. (2020). School bullying victimization and self-rated health and life satisfaction: The gendered buffering effect of educational expectations. Children and Youth Services Review, 116, 105252.CrossRefGoogle Scholar
Chan, N. N., Ahrumugam, P., Scheitauer, H., Schultze-Krumbholz, A., & Ooi, P. B. (2020). A hermeneutic phenomenological study of students’ and school counsellors’ “lived experiences” of cyberbullying and bullying. Computers & Education, 146, 103755.CrossRefGoogle Scholar
Cheng, L., Silva, Y., Hall, D., & Liu, H. (2021). Session-based cyberbullying detection: Problems and challenges. IEEE Internet Computing, 25(2), 66–72.CrossRefGoogle Scholar
Chillemi, K., Abbott, J-A. M., Austin, D. W., & Knowles, A. (2020). A pilot study of an online psychoeducational program on cyberbullying that aims to increase confidence and help-seeking behaviors among adolescents. Cyberpsychology, Behavior, and Social Networking, 23(4), 253–256.CrossRefGoogle ScholarPubMed
Chun, J., Lee, J., Kim, J. & Lee, S. (2020). An international systematic review of cyberbullying measurements. Computers in Human Behavior, 113, 106485.CrossRefGoogle Scholar
Cross, D., Barnes, A., Cardoso, P., Hadwen, K., Shaw, T., Campbell, M., & Slee, P. (2018). Cyber-friendly schools. In Campbell, M. & Bauman, S. (Eds.), Reducing cyberbullying in schools: International evidenced-based best practices (pp. 95–108). Elsevier.CrossRefGoogle Scholar
Cross, D., Shaw, T., Epstein, M., Monks, H., Dooley, J. & Hearn, L. (2011). Cyberbullying in Australia: Is school context related to cyberbullying behavior? In Li, Q., Cross, D., & Smith, P. K. (Eds.), Cyberbullying in the global playground: Research from international perspectives (pp. 75–98). Wiley-Blackwell.Google Scholar
Cross, D., Shaw, T., Hadwen, K., Cardoso, P., Slee, P. … & Barnes, A. (2016). Longitudinal impact of the Cyber Friendly Schools program on adolescents’ cyberbullying behaviour. Aggressive Behavior, 42, 166–180.CrossRefGoogle Scholar
Del Rey, R., Casas, J. A., Ortega-Ruiz, R., Schultze-Krumbholkz, A., Scheithauer, H., Smith, P. K., Thompson, F., Barkoukis, V., Tsorbatzoudis, H., Brighi, A., Guarini, A., Pyzalski, J., & Plichta, P. (2015). Structural validation and cross-cultural robustness of the European Cyberbullying Intervention Project Questionnaire. Computers in Human Behavior, 50, 141–147.CrossRefGoogle Scholar
Del Rey, R., Casas, J. A., & Ortega, R. (2016). Impact of the ConRed program on different cyberbullying roles. Aggressive Behavior, 42, 123–135.CrossRefGoogle Scholar
Dennehy, R., Meaney, S., Walsh, K. A., Sinnott, C., Cronin, M., & Arensman, E. (2020). Young people’s conceptualizations of the nature of cyberbullying: A systematic review and synthesis of qualitative research. Aggression and Violent Behavior, 51, 101379.CrossRefGoogle Scholar
Domínguez-Hernández, F., Bonell, L., & Martínez-González, A. (2018). A systematic literature review of factors that moderate bystanders’ actions in cyberbullying. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 12(4), article 1.CrossRefGoogle Scholar
Dredge, R., Gleeson, J., & Garcia, X de la P. (2014). Cyberbullying in social networking sites: An adolescent victim’s perspective. Computers in Human Behavior, 36, 13–20.CrossRefGoogle Scholar
Elbedour, S., Alqahtani, S., Rihan, I. E. S., Bawalsah, J. A., Booker-Ammah, B., & Turner, J. F. (2020). Cyberbullying: Roles of school psychologists and school counselors in addressing a pervasive social justice issue. Children and Youth Services Review, 109, 104720.CrossRefGoogle Scholar
Ellis, B. J., del Guidice, M., Dishion, T. J., Figueredo, A. J., Gray, P., Griskevicius, V., Hawley, P. H., Jacobs, W. J., James, J., Volk, A. A., & Wilson, D. S. (2012). The evolutionary basis of risk taking behavior: Implications for science, policy, and practice. Developmental Psychology, 48, 598–623.CrossRefGoogle ScholarPubMed
Erreygers, S., Vandebosch, H., Vranjes, I., Baillien, E., & De Witte, H. (2017). The interplay of negative experiences, emotions and affective styles in adolescents’ cybervictimization: A moderated mediation analysis. Computers in Human Behavior, 81, 223–234.CrossRefGoogle Scholar
Espelage, D. L., & Swearer, S. M. (Eds.) (2004). Bullying in American schools: A socio-ecological perspective on prevention and intervention. Erlbaum.CrossRefGoogle Scholar
Fanti, K. A., Demetriou, A. G., & Hawa, V. V. (2012). A longitudinal study of cyberbullying: Examining risk and protective factors. European Journal of Developmental Psychology, 9, 168–181.CrossRefGoogle Scholar
Finkelhor, D., Mitchell, K. J., & Wolak, J. (2000). Online victimization: A report on the nation’s youth. National Center for Missing & Exploited Children.Google Scholar
Frisén, A., Berne, S., Schultze-Krumbholz, A., Scheithauer, H., Naruskov, K., Luik, P., Katzer, C., Erentaite, R., & Zukauskiene, R. (2013). Measurement issues: A systematic review of cyberbullying instruments. In Smith, P. K., & Steffgen, G. (Eds.), Cyberbullying through the new media: Findings from an international network (pp. 37–62). Psychology Press.Google Scholar
Gaffney, H., Farrington, D. P., Espelage, D. L., & Ttofi, M. M. (2019b). Are cyberbullying intervention and prevention programs effective? A systematic and meta-analytical review. Aggression and Violent Behavior, 45, 134–153.CrossRefGoogle Scholar
Gaffney, H., Ttofi, M. M., & Farrington, D. P. (2019a). Evaluating the effectiveness of school-bullying prevention programs: An updated meta-analytical review. Aggression and Violent Behavior, 45, 111–133.CrossRefGoogle Scholar
Gardella, J. H., Fisher, B. W., & Teurbe-Tolon, A. R. (2017). A systematic review and meta-analysis of cyber-victimization and educational outcomes for adolescents. Review of Educational Research, 87(2), 283–308.CrossRefGoogle Scholar
Gibb, Z. G. & Devereux, P. G. (2014). Who does that anyway? Predictors and personality correlates of cyberbullying in college. Computers in Human Behavior, 38, 8–16.CrossRefGoogle Scholar
Gladden, R. M., Vivolo-Kantor, A. M., Hamburger, M. E., & Lumpkin, C. D. (2013). Bullying surveillance among youths: Uniform definitions for public health and recommended data elements, Version 1.0. Atlanta, GA; National Center for Injury Prevention and Control, Centers for Disease Control and Prevention and U.S. Department of Education. Available from www.cdc.gov/violenceprevention/pdf/bullying-factsheet508.pdfGoogle Scholar
González-Cabrera, J., Calvete, E., León-Mejía, A., Pérez-Sancho, C., & Peinado, J. M. (2017). Relationship between cyberbullying roles, cortisol secretion and psychological stress. Computers in Human Behavior, 70, 153–160.CrossRefGoogle Scholar
Goodboy, A. K. & Martin, M. M. (2015). The personality profile of a cyberbully: Examining the Dark Triad. Computers in Human Behavior, 49, 1–4.CrossRefGoogle Scholar
Gradinger, P., Yanagida, T., Strohmeier, D., & Spiel, C. (2016). Effectiveness and sustainability of the ViSC social competence program to prevent cyberbullying and cyber-victimization: Class and individual level moderators. Aggressive Behavior, 42, 181–193.CrossRefGoogle ScholarPubMed
Guillaume, E., & Funder, D. (2016). Theoretical and methodological issues in making cross-national and cross-cultural comparisons. In Smith, P. K., Kwak, K., & Toda, Y. (Eds.), School bullying in different cultures: Eastern and western perspectives (pp. 211–228). Cambridge University Press.CrossRefGoogle Scholar
Hamby, S., Blount, Z., Smith, A., Jones, L., Mitchell, K., & Taylor, E. (2018). Digital poly-victimization: The increasing importance of online crime and harassment to the burden of victimization. Journal of Trauma and Dissociation, 19, 382–398.CrossRefGoogle Scholar
Hamer, A. den, Konijn, E. A., & Keijer, M. G. (2014). Cyberbullying behavior and adolescents’ use of medias with antisocial content: A cyclic process model. Cyberpsychology, Behavior, and Social Networking, 17, 74–81.CrossRefGoogle Scholar
Hamilton, J., Purdy, N., Willems, R. A., Smith, P. K., Culbert, C., Brighi, A., Fiedler, N., Guarini, A., Maneli, C., Menin, D., Scheitauer, H., & Völlink, T. (2020). Using the Quality Circle approach to empower disadvantaged youth in addressing cyberbullying: An exploration across five European countries. Pastoral Care in Education, 38, 254–272.CrossRefGoogle Scholar
Hinduja, S., & Patchin, J. W. (2010). Bullying, cyberbullying, and suicide. Archives of Suicide Research, 14, 206–221.CrossRefGoogle ScholarPubMed
Hinduja, S., & Patchin, J. W. (2015). Bullying beyond the schoolyard: Preventing and responding to cyberbullying (2nd ed.). Sage Publications.Google Scholar
HM Government. (2019). Online Harms White Paper. HMSO, London. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/793360/Online_Harms_White_Paper.pdfGoogle Scholar
Hu, Q., Bernado, A. B. I., Lam, S. W., & Cheang, P. K. (2018). Individualism-collectivism orientations and coping styles of cyberbullying victims in Chinese culture. Current Psychology, 37, 65–72.CrossRefGoogle Scholar
Inchley, J., Currie, D., Young, T., Samdal, O., Torsheim, T., Augustson, L., Mathison, F., Aleman-Diaz, A., Molcho, M., Weber, M., & Barnekow, V. (Eds.) (2016). Growing up unequal: Gender and socioeconomic differences in young people’s health and well-being: Health Behaviour in School-aged Children (HBSC) study: International report from the 2013/2014 survey. WHO Regional Office for Europe.Google Scholar
Inchley, J., Currie, D., Budisavljevic, S., Torsheim, T., Jåstad, A., Cosma, A., Kelly, C., Arnasson, A. M., & Samdal, O. (Eds.) (2020). Spotlight on adolescent health and well-being: Findings from the 2017/2018 Health Behaviour in School-aged Children (HBSC) survey in Europe and Canada. International report Volume 2: Key data. WHO Regional Office for Europe.Google Scholar
Jacobs, N. C., Völlink, T., Dehue, F., & Lechner, L. (2014). Online Pestkoppenstoppen: Systematic and theory-based development of a web-based tailored intervention for adolescent cyberbully victims to combat and prevent cyberbullying. BMC Public Health, 14, 396.CrossRefGoogle ScholarPubMed
Jadambaa, A., Thomas, H. J., Scott, J. G., Graves, N., Brain, D., & Pacella, R. (2019). Prevalence of traditional bullying and cyberbullying among children and adolescents in Australia: A systematic review and meta-analysis. Australian & New Zealand Journal of Psychiatry, 53, 878–888.CrossRefGoogle Scholar
Juvonen, J., & Graham, S. (Eds.) (2001). Peer harassment at school: The plight of the vulnerable and victimised. Guildford.Google Scholar
Kim, S., Colwell, S. R., Kata, A., Boyle, M. H., & Georgiades, K. (2017). Cyberbullying victimization and adolescent mental health: Evidence of differential effects by sex and mental health problem type. Journal of Youth and Adolescence, 47, 661–672.CrossRefGoogle ScholarPubMed
König, A., Gollwitzer, M., & Steffgen, G. (2010). Cyberbullying as an Act of Revenge? Australian Journal of Guidance & Counselling, 20, 210–224.CrossRefGoogle Scholar
Kowalski, R. M., Giumetti, G. W., Schroeder, A. N., & Lattanner, M. R. (2014). Bullying in the digital age: A critical review and meta-analysis of cyberbullying research among youth. Psychological Bulletin, 140, 1073–1137.CrossRefGoogle Scholar
Kwan, I., Dickson, K., Richardson, M., MacDowell, W., Burchett, H., Stansfield, C., Brunton, G., Sutcliffe, K., & Thomas, J. (2020). Cyberbullying and children and young people’s mental health: A systematic map of systematic reviews. Cyberpsychology, Behavior, and Social Networking, 23(2), 72–82.CrossRefGoogle Scholar
Law, D. M., Shapka, J. D., & Olson, B. F. (2010). To control or not to control? Parenting behaviors and adolescent online aggression. Computers in Human Behavior, 26, 1651–1656.CrossRefGoogle Scholar
Lazuras, L., Barkoukis, V., & Tsorbatzoudis, H. (2017). Face-to-face bullying and cyberbullying in adolescents: Trans-contextual effects and role overlap. Technology in Society, 48, 97–101.CrossRefGoogle Scholar
Lee, J. M., Hong, J. S., Yoon, J., Peguero, A. A., & Seok, H. J. (2018). Correlates of adolescent cyberbullying in South Korea in multiple contexts: A review of the literature and implications for research and school practice. Deviant Behavior, 39, 293–308.CrossRefGoogle Scholar
Li, Q., Luo, Y., Hao, Z., Smith, B., Guo, Y., & Tyrone, C. (2021). Risk factors of cyberbullying perpetration among school-aged children across 41 countries: A perspective of Routine Activity Theory. International Journal of Bullying Prevention, 3, 168–180.CrossRefGoogle Scholar
Livingstone, S., Haddon, L., Görzig, A., & Ólafsson, K. (2011). Risks and safety on the internet: The perspective of European children. Full findings. EU Kids Online.Google Scholar
Lozano-Blasco, R., Cortés-Pascual, A., & Latorre-Martínez, M. P. (2020). Being a cybervictim and a cyberbully – The duality of cyberbullying: A meta-analysis. Computers in Human Behavior, 111, 106444.CrossRefGoogle Scholar
Marciano, L., Schulz, P. J., & Camerini, A-L. (2020). Cyberbullying perpetration and victimization in youth: A meta-analysis of longitudinal studies. Journal of Computer-Mediated Communication, 25, 163–181.CrossRefGoogle Scholar
McGeough, B. (2020). An analysis of statewide anti‑bullying laws employing the Iowa Safe Schools Law as a case study. Child and Adolescent Social Work Journal, 39, 97–106.Google Scholar
Menesini, E., Nocentini, A., Palladino, B. E., Frisén, A., Berne, S., Ortega, R. R., Calmaestra, J., Scheithauer, H., Schultze-Krumbholz, A., Luik, P., Naruskov, K., Blaya, C., Berthaud, J., & Smith, P. K. (2012). Cyberbullying definition among adolescents: A comparison across six European countries. Cyberpsychology, Behavior and Social Networking, 15, 455–463.CrossRefGoogle ScholarPubMed
Menesini, E., Nocentini, A., Palladino, B. E., Scheithauer, H., Schultze-Krumbholz, A., Frisén, A., Berne, S., Luik, P., Naruskov, K., Ortega, R., Calmaestra, J., & Blaya, C. (2013). Definitions of cyberbullying. In Smith, P. K. & Steffgen, G. (Eds.), Cyberbullying through the new media: Findings from an international network (pp. 23–36). Psychology Press.Google Scholar
Menesini, E., Palladino, B. E., & Nocentini, A. (2016). Online and school based intervention to prevent cyberbullying among adolescents. In Völlink, T., Dehue, F., & McCuckin, C. (Eds.), Cyberbullying: From theory to intervention (pp. 56–175). Routledge.Google Scholar
Modecki, K. L., Minchin, J., Harbaugh, A. G., Guerra, N. G., & Runions, K. C. (2014). Bullying prevalence across contexts: A meta-analysis measuring cyber and traditional bullying. Journal of Adolescent Health, 55, 602–611.CrossRefGoogle ScholarPubMed
Monks, C. P., Ortega, R., Robinson, S., & Worlidge, P. (2009). Cyberbullying among primary school-aged pupils. Kwartalnik Pedagogiczny, 214, 167–181.Google Scholar
Mweru, M. (2021). Bullying research and intervention in sub-Saharan Africa. In Smith, P. K. & O’Higgins Norman, J. (Eds.), The Wiley Blackwell handbook of bullying: A comprehensive and international review of research and intervention (pp. 634–651). Wiley.CrossRefGoogle Scholar
Olweus, D., & Limber, S. P. (2018). Some problems with cyberbullying research. Current Opinion in Psychology, 19, 139–143.CrossRefGoogle ScholarPubMed
Palladino, B. E., Nocentini, A., & Menesini, E. (2015). Psychometric properties of the Florence CyberBullying-CyberVictimization Scales. Cyberpsychology, Behavior, and Social Networking, 18(2), 112–119.CrossRefGoogle ScholarPubMed
Patchin, J. W., & Hinduja, S. (2015). Measuring cyberbullying: Implications for research. Aggression and Violent Behavior, 23, 69–74.CrossRefGoogle Scholar
Peter, I.-K., & Petermann, F. (2018). Cyberbullying: A concept analysis of defining attributes and additional influencing factors. Computers in Human Behavior, 86, 350–366.CrossRefGoogle Scholar
Pozzoli, T., & Gini, G. (2020). Behavior during cyberbullying episodes: Initial validation of a new self‐report scale. Scandinavian Journal of Psychology, 61, 22–29.CrossRefGoogle ScholarPubMed
Przybylski, A., & Bowes, L. (2017). Cyberbullying and adolescent well-being in England: A population-based cross-sectional study. Lancet Child and Adolescent Health, 1, 19–26.CrossRefGoogle Scholar
Purdy, N., & Spears, B. (2020) Co-participatory approaches to research with children and young people. Pastoral Care in Education, 38(3), 187–190.CrossRefGoogle Scholar
Pyzalski, J. (2012). From cyberbullying to electronic aggression: Typology of the phenomenon. Emotional and Behavioural Difficulties, 17, 305–317.CrossRefGoogle Scholar
Quintana-Orts, C., Rey, L., Chamizo-Nieto, M. T., & Worthington, E. L. (2020). A serial mediation model of the relationship between cybervictimization and cyberaggression: The role of stress and unforgiveness motivations. International Journal of Environmental Research and Public Health, 17.CrossRefGoogle ScholarPubMed
Rivers, I., & Noret, N. (2010). “I h8 u”: Findings from a five year study of text and email bullying. British Educational Research Journal, 36, 643–671.CrossRefGoogle Scholar
Rosa, H., Pereira, N., Ribeiro, R., Ferreira, P. C., Carvalho, J. P., Oliveira, S., Coheur, L., Paulino, P., Veiga Simão, A. M., & Trancoso, I. (2019). Automatic cyberbullying detection: A systematic review. Computers in Human Behavior, 93, 333–335.CrossRefGoogle Scholar
Ruangnapakul, N., Salam, Y. D., & Shawkat, A. R. (2019). A systematic analysis of cyber bullying in Southeast Asia countries. International Journal of Innovative Technology and Exploring Engineering, 8(4S), 104–111.Google Scholar
Salmivalli, C., Karna, A., & Poskiparta, E. (2011). Counteracting bullying in Finland: The KiVa program and its effects on different forms of being bullied. International Journal of Behavioral Development, 35, 405–411.CrossRefGoogle Scholar
Salmivalli, C., & Poskiparta, E. (2012). KiVa antibullying program: Overview of evaluation studies based on a randomized controlled trial and national rollout in Finland. International Journal of Conflict and Violence, 6, 294–302.Google Scholar
Samara, M., & El Asam, A. (2021). Bullying research and intervention in the Arab world. In Smith, P. K. & O’Higgins Norman, J. (Eds.), The Wiley Blackwell handbook of bullying: A comprehensive and international review of research and intervention (pp. 608–633). Wiley.CrossRefGoogle Scholar
Schultze-Krumbholz, A., Zagorsck, P., & Scheithauer, H. (2018). A school-based cyberbullying preventive intervention approach: The Media Heroes program. In Campbell, M. & Bauman, S. (Eds.), Reducing cyberbullying in schools: International evidenced-based best practices (pp. 145–158). Academic Press.CrossRefGoogle Scholar
Ševčíková, A., & Šmahel, D. (2009). Online harassment and cyberbullying in the Czech Republic: Comparison across age groups. Zeitschrift für Psychologie/Journal of Psychology, 217, 227–229.CrossRefGoogle Scholar
Skilbred-Fjeld, S., Reme, S. E., & Mossige, S. (2020). Cyberbullying involvement and mental health problems among late adolescents. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 14(1), Article 5.CrossRefGoogle Scholar
Slonje, R., & Smith, P. K. (2008). Cyberbullying: Another main type of bullying? Scandinavian Journal of Psychology, 49, 147–154.CrossRefGoogle ScholarPubMed
Slonje, R., Smith, P. K., & Frisén, A. (2013). The nature of cyberbullying, and strategies for prevention. Computers in Human Behavior, 29, 26–32.CrossRefGoogle Scholar
Šmahel, D., Machackova, H., Mascheroni, G., Dedkova, L., Staksrud, E., Ólafsson, K., Livingstone, S., & Hasebrink, U. (2020). EU Kids Online 2020: Survey results from 19 countries. EU Kids Online. https://doi.org/10.21953/lse.47fdeqj01ofoCrossRefGoogle Scholar
Smith, P. K. (2018). Commentary. In Campbell, M. & Bauman, S. (Eds.), Reducing cyberbullying in schools (pp. 257–272). Elsevier.CrossRefGoogle Scholar
Smith, P. K. (ed.) (2019). Making an impact on school bullying: Interventions and recommendations. Routledge.CrossRefGoogle Scholar
Smith, P. K., & Berkkun, F. (2017). How research on cyberbullying has developed. In Mc Guckin, C., & Corcoran, L. (Eds.). Bullying and cyberbullying: Prevalence, psychological impacts and intervention strategies (pp. 11–27). Nova Science.Google Scholar
Smith, P. K., & Berkkun, F. (2020). How prevalent is contextual information in research on school bullying? Scandinavian Journal of Psychology, 61, 17–21.CrossRefGoogle ScholarPubMed
Smith, P. K., del Barrio, C., & Tokunaga, R. (2013). Definitions of bullying and cyberbullying: How useful are the terms? In Bauman, S., Walker, J, & Cross, D. (Eds.), Principles of cyberbullying research: Definition, methods, and measures (pp. 64–86). Routledge.Google Scholar
Smith, P. K., Görzig, A., & Robinson, S. (2018). Issues of cross-cultural variations in cyber-bullying across Europe and beyond. Media@LSE Working Paper Series, WP 49, 1–28.Google Scholar
Smith, P. K., Görzig, A., & Robinson, S. (2019). Cyberbullying in schools: Cross-cultural issues. In Giumetti, G. W. & Kowalski, R. M. (Eds.), Cyberbullying in schools, workplaces, and romantic relationships (pp. 49–68). Routledge.CrossRefGoogle Scholar
Smith, P. K., López-Castro, L., Robinson, S., & Görzig, A. (2019). Consistency of gender differences in bullying in different cross-cultural surveys. Aggression and Violent Behavior, 45, 33–40.CrossRefGoogle Scholar
Smith, P. K., Mahdavi, J. M., Fisher, S., Russell, S, & Tippett, N. (2008). Cyberbullying: It’s nature and impact in secondary school pupils. Journal of Child Psychology and Psychiatry, 49(4), 376–385.CrossRefGoogle Scholar
Smith, P. K., Robinson, S., & Slonje, R. (2021). The school bullying research program: Why and how it has developed. In Smith, P. K. & O’Higgins Norman, J. (Eds.), The Wiley Blackwell handbook of bullying: A comprehensive and international review of research and intervention (pp. 42–59). Wiley.CrossRefGoogle Scholar
Smith, P. K., & Steffgen, (Eds.) (2013). Cyberbullying through the new media: Findings from an international network. Psychology Press.CrossRefGoogle Scholar
Society for Research in Child Development. (2020). New sociocultural policy enacted across all SRCD journals. www.srcd.org/news/new-sociocultural-policy-enacted-across-all-srcd-journalsGoogle Scholar
Sorrentino, A., Baldry, A. C., Farrington, D. P., & Blaya, C. (2019). Epidemiology of cyberbullying across Europe: Differences between countries and genders. Educational Sciences: Theory & Practice, 19(2), 74–91.Google Scholar
Spears, B., & Taddeo, C. (2021). Coping with cyberbullying. In Smith, P. K. & O’Higgins Norman, J. (Eds.), The Wiley Blackwell handbook of bullying: A comprehensive and international review of research and intervention (pp. 240–259). Wiley.CrossRefGoogle Scholar
Spiel, C., Schober, B., & Strohmeier, D. (2018). Implementing intervention research into public policy – The “I 3-Approach”. Prevention Science, 19, 337–346.CrossRefGoogle ScholarPubMed
Svensson, M., & Beckman, L. (2021). Economic evaluation of bullying prevention programs. In Smith, P. K. & O’Higgins Norman, J. (Eds.), The Wiley Blackwell handbook of bullying: A comprehensive and international review of research and intervention (pp. 707–724). Wiley.CrossRefGoogle Scholar
Thornberg, R. (2011). “She’s weird!” – The social construction of bullying in school: A review of qualitative research. Children & Society, 25, 258–267.CrossRefGoogle Scholar
Tokunaga, R. S. (2010). Following you home from school: A critical review and synthesis of research on cyberbullying victimization. Computers in Human Behavior, 26, 277–287.CrossRefGoogle Scholar
Vaillancourt, T., & Palamarchuk, I. S. (2021). Neurobiological factors of bullying victimization. In Smith, P. K. & O’Higgins Norman, J. (Eds.), The Wiley Blackwell handbook of bullying: A comprehensive and international review of research and intervention (pp. 399–414). Wiley.CrossRefGoogle Scholar
Vandebosch, H., Simulioniene, R., Marczak, M., Vermeulen, A., & Bonetti, L. (2013). The role of the media. In Smith, P. K. & Steffgen, G. (Eds.), Cyberbullying through the new media: Findings from an international network (pp. 99–118). Psychology Press.Google Scholar
Vandebosch, H., & Green, L. (Eds.) (2019). Narrative approaches in research and interventions addressing cyberbullying. Springer.Google Scholar
Van Geel, M., & Vedder, P. (2019). Does cyberbullying predict internalizing problems and conduct problems when controlled for traditional bullying? Scandinavian Journal of Psychology, 61, 307–311.CrossRefGoogle ScholarPubMed
Van Geel, M., Vedder, P., & Tanilon, J. (2014). Relationship between peer victimization, cyberbullying, and suicide in children and adolescents: A meta-analysis. JAMA Pediatrics, 168, 435–442.CrossRefGoogle ScholarPubMed
Van Geel, M., Goemans, A., Toprak, F., & Vedder, P. (2017). Which personality traits are related to traditional bullying and cyberbullying? A study with the Big Five, Dark Triad and sadism. Personality and Individual Differences, 106, 231–235.CrossRefGoogle Scholar
Van Hee, C., Jacobs, G., Emmery, C., Desmet, B., Lefever, E., Verhoeven, B., De Pauw, G., Daelemans, W. & Hoste, V. (2018). Automatic detection of cyberbullying in social media text. PLoS ONE, 13(10), e0203794.CrossRefGoogle ScholarPubMed
Varela, J., Madriaza, P., & Sánchez, P. A. (2021). Bullying research and intervention in South America. In Smith, P. K. & O’Higgins Norman, J. (Eds.), The Wiley Blackwell handbook of bullying: A comprehensive and international review of research and intervention (pp. 652–675). Wiley.CrossRefGoogle Scholar
Vivolo-Kantor, A. M., Martell, B. N., Holland, K. M., & Westby, R. (2014). A systematic review and content analysis of bullying and cyber-bullying measurement strategies. Aggression and Violent Behavior, 19, 423–434.CrossRefGoogle ScholarPubMed
Wang, M-J., Yogeeswaran, K., Andrews, N. P., Hawi, D. R., & Sibley, C. G. (2019). How common is cyberbullying among adults? Exploring gender, ethnic, and age differences in the prevalence of cyberbullying. Cyberpsychology, Behavior, and Social Networking, 22(11), 736–741.CrossRefGoogle ScholarPubMed
Wang, X., Yang, L., Yang, J., Wang, P., & Lei, L. (2017). Trait anger and cyberbullying among young adults: A moderated mediation model of moral disengagement and moral identity. Computers in Human Behavior, 73, 519–526.CrossRefGoogle Scholar
Whittaker, E., & Kowalski, R. M. (2015). Cyberbullying via social media. Journal of School Violence, 14, 11–29.CrossRefGoogle Scholar
Wolke, D., Lee, K., & Guy, A. (2017). Cyberbullying: A storm in a teacup? Europeasn Child and Adolescent Psychiatry, 26, 899–908.CrossRefGoogle ScholarPubMed
Ybarra, M. L. (2004). Linkages between depressive symptomatology and internet harassment among young regular Internet users. Cyberpsychology & Behavior, 7, 247–257.CrossRefGoogle ScholarPubMed
Ybarra, M. L., Prescott, T. L., & Espelage, D. L. (2016). Stepwise development of a text messaging-based bullying prevention program for middle school students (BullyDown). JMIR Mhealth Uhealth, 4(2), e60.CrossRefGoogle ScholarPubMed
Yeager, D. S., Fong, C. J., Lee, H. Y., & Espelage, D. L. (2015). Declines in efficacy of anti-bullying programs among older adolescents: Theory and a three-level meta-analysis. Journal of Applied Developmental Psychology, 37, 36–51.CrossRefGoogle Scholar
Zych, I., Baldry, A. C., Farrington, D. P., & Llorent, V. J. (2019b). Are children involved in cyberbullying low on empathy? A systematic review and meta-analysis of research on empathy versus different cyberbullying roles. Aggression and Violent Behavior, 45, 83–97.CrossRefGoogle Scholar
Zych, I., Farrington, D. P., & Ttofi, M. M. (2019a). Protective factors against bullying and cyberbullying: A systematic review of meta-analyses. Aggression and Violent Behavior, 45, 4–19.CrossRefGoogle Scholar
Zych, I., Ortega-Ruiz, R., & del Rey, R. (2015). Scientific research on bullying and cyberbullying: Where have we been and where are we going? Aggression and Violent Behavior, 23, 1–21.CrossRefGoogle Scholar
References
Alfasi, Y. (2019). The grass is always greener on my friends’ profiles: The effect of Facebook social comparison on state self-esteem and depression. Personality and Individual Differences, 147, 111–117. https://doi.org/10.1016/j.paid.2019.04.032CrossRefGoogle Scholar
Altman, I., & Taylor, D. A. (1973). Social penetration: The development of interpersonal relationships. Holt, Rinehart and Winston.Google Scholar
Baumeister, R. F. (1982). A self-presentational view of social phenomena. Psychological Bulletin, 91(1), 3–26. https://doi/org/10.1037/0033-2909.91.1.3CrossRefGoogle Scholar
Baumeister, R. F., & Leary, M. R. (1995). The need to belong: Desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117(3), 497–529. doi: 10.1037/0033-2909.117.3.497CrossRefGoogle ScholarPubMed
Bessiere, K., Kiesler, S., Kraut, R., & Boneva, B. (2008). Effects of Internet use and social resources on changes in depression. Information, Communication & Society, 11(1), 47–70. doi: 10.1080/13691180701858851CrossRefGoogle Scholar
Blomfield Neira, C. J., & Barber, B. L. (2014). Social networking site use: Linked to adolescents’ social self-concept, self-esteem, and depressed mood. Australian Journal of Psychology, 66(1), 56–64. doi: 10.1111/ajpy.12034CrossRefGoogle Scholar
Burgoon, J. K. (1976). The unwillingness to communicate scale: Development and validation. Communication Monographs, 43, 60–69. https://doi.org/10.1080/03637757609375916CrossRefGoogle Scholar
Burke, M., & Kraut, R. E. (2016). The relationship between Facebook use and well-being depends on communication type and tie strength. Journal of Computer-Mediated Communication, 21, 265–281. doi: 10.1111/jcc4.12162CrossRefGoogle Scholar
Burke, M., Kraut, R., & Marlow, C. (2011). Social capital on Facebook: Differentiating uses and users. In Tan, D., Fitzpatrick, G., Gutwin, C., Begole, B., & Kellogg, W. A. (Eds.), Proceedings of the International Conference on Human Factors in Computing Systems (pp. 571–580). Association for Computing Machinery. doi: 10.1145/1978942.1979023Google Scholar
Chen, H.-T., & Li, X. (2017). The contribution of mobile social media to social capital and psychological well-being: Examining the role of communicative use, friending and self-disclosure. Computers in Human Behavior, 75, 958–965. http://dx.doi.org/10.1016/j.chb.2017.06.011CrossRefGoogle Scholar
Chua, Y. P., & Chua, Y. P. (2017). Do computer-mediated communication skill, knowledge and motivation mediate the relationships between personality traits and attitude toward Facebook? Computers in Human Behavior, 70, 51–59. https://doi.org/cg43CrossRefGoogle Scholar
Cohen, S., & Wills, T. A. (1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98(2), 310–357. doi: 10.1037/0033-2909.98.2.310CrossRefGoogle ScholarPubMed
Cole, D. A., Nick, E. A., Varga, G., Smith, D., Zelkowitz, R. L., Ford, M. A., & Ledecsi, A. (2019). Are aspects of Twitter use associated with reduced depressive symptoms? The moderating role of in-person social support. Cyberpsychology, Behavior, and Social Networking, 22(11), 692–99. https://doi.org/10.1089/cyber.2019.0035CrossRefGoogle ScholarPubMed
Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268. doi: 10.1207/S15327965PLI1104_01CrossRefGoogle Scholar
Deters, F. G., & Mehl, M. R. (2012). Does posting Facebook status updates increase or decrease loneliness? An online social networking experiment. Social Psychology and Personality Science, 4(5), 579–586. doi: 10.1177/1948550612469233CrossRefGoogle Scholar
de Vries, D. A., & Kühne, R. (2015). Facebook and self-perception: Individual susceptibility to negative social comparison on Facebook. Personality and Individual Differences, 85, 217–221. doi: 10.1016/j.paid.2015.05.029CrossRefGoogle Scholar
de Vries, D. A., Möller, M., Wieringa, M. S., Eigenraam, A. W., & Hamelink, K. (2018). Social comparison as the thief of joy: Emotional consequences of viewing strangers’ Instagram posts. Media Psychology, 21(2), 222–245. https://doi.org/10.1080/15213269.2016.1267647CrossRefGoogle Scholar
Dindia, K. (2000). Self-disclosure, identity, and relationship development: A dialectical perspective. In Dindia, K. & Ducks, S. W. (Eds.), Communication and personal relationship (pp. 147–162). Wiley.Google Scholar
Ellison, N. B, Gray, R., Lampe, C., & Fiore, A. T. (2014). Social capital and resource requests on Facebook. New Media Society, 16(7), 1104–1121. doi: 10.1177/1461444814543998CrossRefGoogle Scholar
Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends”: Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12(4), 1143–1168. doi: 10.1111/j.1083-6101.2007.00367.xCrossRefGoogle Scholar
Ellison, N. B., Vitak, J., Gray, R., & Lampe, C. (2014). Cultivating social resources on social network sites: Facebook relationship maintenance behaviors and their role in social capital processes. Journal of Computer-Mediated Communication, 19, 855–870. doi: 10.1111/jcc4.12078CrossRefGoogle Scholar
Eşkisu, M., & Hoşoğlu, R., & Rasmussen, K. (2017). An investigation of the relationship between Facebook usage, Big Five, self-esteem and narcissism. Computers in Human Behavior, 69, 294–301. http://dx.doi.org/10.1016/j.chb.2016.12.036%200747–5632CrossRefGoogle Scholar
Feinstein, B. A., Hershenberg, R., Bhatia, V., Latack, J. A., Meuwly, N., & Davila, J. (2013). Negative social comparison on Facebook and depressive symptoms: Rumination as a mechanism. Psychology of Popular Media Culture, 2(3), 161–170. doi: 10.1037/a0033111CrossRefGoogle Scholar
Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7(2), 117–140. doi: 10.1177/001872675400700202CrossRefGoogle Scholar
Frison, E., Bastin, M., Patricia Bijttebier, P., & Eggermont, S. (2019). Helpful or harmful? The different relationships between private Facebook interactions and adolescents’ depressive symptoms. Media Psychology, 22(2), 244–272, https://doi.org/10.1080/15213269.2018.1429933CrossRefGoogle Scholar
Frison, E., & Eggermont, S. (2016a). Exploring the relationships between different types of Facebook use, perceived online social support, and adolescents’ depressed mood. Social Science Computer Review, 34(2), 153–171. https://doi.org/10.1177/0894439314567449CrossRefGoogle Scholar
Frison, E., & Eggermont, S. (2016b). “Harder, better, faster, stronger”: Negative comparison on Facebook and adolescents’ life satisfaction are reciprocally related. Cyberpsychology, Behavior, and Social Networking, 19(3), 158–164. https://doi.org/10.1089/cyber.2015.0296CrossRefGoogle ScholarPubMed
Frison, E., & Eggermont, S. (2017). Browsing, posting, and liking on Instagram: The reciprocal relationships between different types of Instagram use and adolescents’ depressed mood. Cyberpsychology, Behavior, and Social Networking, 20(10), 603–609. https://doi.org/10.1089/cyber.2017.0156CrossRefGoogle ScholarPubMed
Gentile, B., Twenge, J. M., Freeman, E. C., & Campbell, W. K. (2012). The effect of social networking websites on positive self-views: An experimental investigation. Computers in Human Behavior, 28, 1929–1933. http://dx.doi.org/10.1016/j.chb.2012.05.012CrossRefGoogle Scholar
Gerson, J., Plagnol, A. C., & Corr, P. J. (2016). Subjective well-being and social media use: Do personality traits moderate the impact of social comparison on Facebook? Computers in Human Behavior, 63, 813–822. http://dx.doi.org/10.1016/j.chb.2016.06.023CrossRefGoogle Scholar
Goldman, B. M., & Kernis, M. H. (2002). Role of authenticity in healthy psychological functioning and subjective well-being. Annals of the American Psychotherapy Association, 5(6), 18–20.Google Scholar
Gonzales, A. L., & Hancock, J. T. (2011). Mirror, mirror on my Facebook Wall: Effects of exposure to Facebook on self-esteem. Cyberpsychology, Behavior, and Social Networking, 14(1–2), 79–83. https://doi.org/10.1089/cyber.2009.0411CrossRefGoogle ScholarPubMed
Greitemeyer, T., Mügge, D. O., & Bollermann, I. (2014). Having responsive Facebook friends affects the satisfaction of psychological needs more than having many Facebook friends. Basic and Applied Social Psychology, 36(3), 252–258. https://doi.org/10.1080/01973533.2014.900619CrossRefGoogle Scholar
House, J. S., Umberson, D., & Landis, K. R. (1988). Structures and processes of social support. Annual Review Sociology, 14, 293–318. doi: 10.1146/annurev.so.14.080188.001453CrossRefGoogle Scholar
Huang, C. (2017). Time spent on social network sites and psychological well-being: A meta-analysis. Cyberpsychology, Behavior, and Social Networking, 20(6), 346–354. doi: 10.1089/cyber.2016.0758CrossRefGoogle ScholarPubMed
Işbulan, O. (2011). Opinions of university graduates about social networks according to their personal characteristics. TOJET: The Turkish Online Journal of Educational Technology, 10(2), 184–189.Google Scholar
Jin, B. (2013). How lonely people use and perceive Facebook. Computers in Human Behavior, 29, 2463–2470. doi: 10.1016/j.chb.2013.05.034CrossRefGoogle Scholar
Jung, Y., Song, H., & Vorderer, P. (2012). Why do people post and read personal messages in public? The motivation of using personal blogs and its effects on users’ loneliness, belonging, and well-being. Computers in Human Behavior, 28, 1626–1633. http://dx.doi.org/10.1016/j.chb.2012.04.001CrossRefGoogle Scholar
Katz, E., Blumler, J. G., & Gurevitch, M. (1973–1974). Uses and gratifications research. Public Opinion Quarterly, 37(4), 509–523. https://doi.org/10.1086/268109CrossRefGoogle Scholar
Kim, J., & Dindia, K. (2011). Online self-disclosure: A review of research. In Wright, K. B. & Webb, L. M. (Eds.), Computer-mediated communication in personal relationships (pp. 156–180). Peter Lang Publishing.Google Scholar
Kim, J., & Lee, J.-E. R. (2011). The Facebook paths to happiness: Effects of the number of Facebook friends and self-presentation on subjective well-being. Cyberpsychology, Behavior, and Social Networking, 14(6), 359–364. https://doi.org/10.1089/cyber.2010.0374CrossRefGoogle ScholarPubMed
Kim, K.-S., Sin, S.-C. J., & Tsai, T.-I. (2014). Individual differences in social media use for information seeking. The Journal of Academic Librarianship, 40, 171–178. https://doi.org/f5z4f4CrossRefGoogle Scholar
Kraut, R. E., & Burke, M. (2015). Internet use and psychological well-being: Effects of activity and audience. Communications of the ACM, 58(12), 94–100. doi: 10.1145/2739043CrossRefGoogle Scholar
Kraut, R., Kiesler, S., Boneva, B., Cummings, J., Helgeson, V., & Crawford, A. (2002). Internet paradox revisited. Journal of Social Issues, 58(1), 49–74. doi: 10.1111/1540-4560.00248CrossRefGoogle Scholar
Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukopadhyay, T., & Scherlis, W. (1998). Internet paradox: A social technology that reduces social involvement and psychological well-being? American Psychologist, 53, 1017–1031.CrossRefGoogle ScholarPubMed
Lamp, S. J., Cugle, A., Silverman, A. L., Thomas, M. T., Liss, M., & Erchull, M. J. (2019). Picture perfect: The relationship between selfie behaviors, self-objectification, and depressive symptoms. Sex Roles, 81, 704–712. https://doi.org/10.1007/s11199-019-01025-zCrossRefGoogle Scholar
Leary, M. R., & Kowalski, R. M. (1990). Impression management: A literature review and two-component model. Psychological Bulletin, 107(1), 34–47. doi: 10.1037/0033-2909.107.1.34CrossRefGoogle Scholar
Lian, S-L., Sun, X-J., Yang, X-J., & Zhou, Z-K. (2018). The effect of adolescents’ active social networking site use on life satisfaction: The sequential mediating roles of positive feedback and relational certainty. Current Psychology. https://doi.org/10.1007/s12144-018-9882-yCrossRefGoogle Scholar
Liu, D., Baumeister, R. F., Yang, C.-c., & Hu, B. (2019). Digital communication media use and psychological well-being: A meta-analysis. Journal of Computer-Mediated Communication, 24, 259–274. https://doi.org/10.1093/ccc/zmz013CrossRefGoogle Scholar
Liu, J., Li, C., Carcioppolo, N., & North, M. (2016). Do our Facebook friends make us feel worse? A study of social comparison and emotion. Human Communication Research, 42, 619–640. doi: 10.1111/hcre.12090CrossRefGoogle Scholar
Lup, K., Trub, L., & Rosenthal, L. (2015). Instagram #Instasad? Exploring associations among Instagram use, depressive symptoms, negative social comparison, and strangers followed. Cyberpsychology, Behavior, and Social Networking, 18(5), 247–252. https://doi.org/10.1089/cyber.2014.0560CrossRefGoogle ScholarPubMed
Manago, A. M., & Melton, C. J. (2020). Emerging adults’ views on masspersonal self-disclosure and their bridging social capital on Facebook. Journal of Adolescent Research, 35(1), 111–146. doi: 10.1177/0743558419883789CrossRefGoogle Scholar
McDaniel, B. T., & Coyne, S. M. (2016). “Technoference”: The interference of technology in couple relationships and implications for women’s personal and relational well-being. Psychology of Popular Media Culture, 5(1), 85–98. http://dx.doi.org/10.1037/ppm0000065CrossRefGoogle Scholar
McKenna, K., & Bargh, J. (2000). Plan 9 from cyberspace: The implications of the Internet for personality and social psychology. Personality and Social Psychology Review, 4, 57–75. doi: 10.1207/S15327957PSPR0401_6CrossRefGoogle Scholar
McKenna, K. Y. A., Green, A. S., & Gleason, M. E. J. (2002). Relationship formation on the Internet: What’s the big attraction. Journal of Social Issues, 58, 9–31. https://doi.org/10.1111/1540-4560.00246CrossRefGoogle Scholar
Moore, K., & McElroy, J. C. (2012). The influence of personality on Facebook usage, wall postings, and regret. Computers in Human Behavior, 28, 267–274. doi: https://doi.org/10.1016/j.chb.2011.09.009CrossRefGoogle Scholar
Mull, I. R., & Lee, S. (2014). “PIN” pointing the motivational dimensions behind Pinterest. Computers in Human Behavior, 33, 192–200. doi: 10.1016/j.chb.2014.01.011CrossRefGoogle Scholar
Muscanell, N. L., & Guadagno, R. E. (2012). Make new friends or keep the old: Gender and personality differences in social networking use. Computers in Human Behavior, 28, 107–112. https://doi.org/b2mhxpCrossRefGoogle Scholar
Nesi, J., Choukas-Bradley, S., & Prinstein, M. J. (2018). Transformation of adolescent peer relations in the social media context: Part 1 – A theoretical framework and application to dyadic peer relationships. Clinical Child and Family Psychology Review, 21(3), 267–294. https://doi.org/10.1007/s10567-018-0261-xCrossRefGoogle ScholarPubMed
Noon, E. J., & Meier, A. (2019). Inspired by friends: Adolescents’ network homophily moderates the relationship between social comparison, envy, and inspiration on Instagram. Cyberpsychology, Behavior, and Social Networking, 22(12). 787–793. https://doi.org/10.1089/cyber.2019.0412CrossRefGoogle ScholarPubMed
Ong, E. Y. L., Ang, R. P., Ho, J. C. M., Lim, J. C. Y., Goh, D. H., Lee, C. S., & Chua, A. Y. K. (2011). Narcissism, extraversion and adolescents’ self-presentation on Facebook. Personality and Individual Differences, 50, 180–185. https://doi.org/bn9944CrossRefGoogle Scholar
Orben, A. C., & Dunbar, R. I. M. (2017). Social media and relationship development: The effect of valence and intimacy of posts. Computers in Human Behavior, 73, 489–498. http://dx.doi.org/10.1016/j.chb.2017.04.006CrossRefGoogle Scholar
Orr, E. S., Sisic, M., Ross, C., Simmering, M. G., Arseneault, J. M., & Orr, R. R. (2009). The influence of shyness on the use of Facebook in an undergraduate sample. CyberPsychology and Behavior, 12, 337–340. http://dx.doi.org/10.1089/cpb.2008.0214.CrossRefGoogle Scholar
Park, S. Y., & Baek, Y. M. (2018). Two faces of social comparison on Facebook: The interplay between social comparison orientation, emotions, and psychological well-being. Computers in Human Behavior, 79, 83–93. doi: 10.1016/j.chb.2017.10.028CrossRefGoogle Scholar
Peter, J., Valkenburg, P. M., & Schouten, A. P. (2005). Developing a model of adolescent friendship formation on the Internet. CyberPsychology & Behavior, 8, 423–430. doi: 10.1089/cpb.2005.8.423CrossRefGoogle Scholar
Pew Research Center. (2019, June 12). Social media fact sheet. Retrieved from www.pewresearch.org/internet/fact-sheet/social-media/Google Scholar
Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. New York: Simon & Chuster Paperbacks.Google Scholar
Reinecke, L., & Trepte, S. (2014). Authenticity and well-being on social network sites: A two-wave longitudinal study on the effects of online authenticity and the positivity bias in SNS communication. Computers in Human Behavior, 30, 95–102. http://dx.doi.org/10.1016/j.chb.2013.07.030CrossRefGoogle Scholar
Roberts, J. A., & David, M. E. (2016). My life has become a major distraction from my cell phone: Partner phubbing and relationship satisfaction among romantic partners. Computers in Human Behavior, 54, 134–141. doi: 10.1016/j.chb.2015.07.058CrossRefGoogle Scholar
Scherr, S., Toma, C. L., & Schuster, B. (2019). Depression as a predictor of Facebook surveillance and envy, longitudinal evidence from a cross-lagged panel study in Germany. Journal of Media Psychology, 31(4), 196–202. https://doi.org/10.1027/1864-1105/a000247CrossRefGoogle Scholar
Schmuck, D., Karsay, K., Matthes, J., & Stevic, A. (2019). “Looking up and feeling down”: The influence of mobile social networking site use on upward social comparison, self-esteem, and well-being of adult smartphone users. Telematics and Informatics, 42. Advance online publication. https://doi.org/10.1016/j.tele.2019.101240CrossRefGoogle Scholar
Seo, M., Kim, J., & Yang, H. (2016). Frequent interaction and fast feedback predict perceived social support: Using crawled and self-reported data of Facebook users. Journal of Computer-Mediated Communication, 21, 282–297. https://doi.org/10.1111/jcc4.12160CrossRefGoogle Scholar
Sheldon, P. (2008). The relationship between unwillingness to communicate and students’ Facebook use. Journal of Media Psychology: Theories, Methods, and Applications, 20, 67–75. doi:10.1027/1864-1105.20.2.67CrossRefGoogle Scholar
Sheldon, P., Antony, M. G., & Ware, L. (2021). Baby Boomers’ use of Facebook and Instagram: Uses and gratifications and contextual age indicators. Heliyon, 7(4). doi:10.1016/j.heliyon.2021.e06670CrossRefGoogle ScholarPubMed
Sheldon, P., & Bryant, K. (2016). Instagram: Motives for its use and relationship to narcissism and contextual age. Computers in Human Behavior, 58, 89–97. doi: 10.1016/j.chb.2015.12.059CrossRefGoogle Scholar
Sheldon, P., & Newman, M. (2019). Instagram and American teens: Understanding motives for its use and relationship to excessive reassurance-seeking and interpersonal rejection. The Journal of Social Media in Society, 8, 1–16.Google Scholar
Sheldon, P., Rauschnabel, P., Antony, M. G., & Car, S. (2017). A cross-cultural comparison of Croatian and American social network sites: Exploring cultural differences in motives for Instagram use. Computers in Human Behavior, 75, 643–651. doi: 10.1016/j.chb.2017.06.009CrossRefGoogle Scholar
Shen, J., Brdiczka, O., & Liu, J. (2015). A study of Facebook behavior: What does it tell about your neuroticism and extraversion? Computers in Human Behavior, 45, 32–38. doi: 10.1016/j.chb.2014.11.067CrossRefGoogle Scholar
Sherman, D. K., Cohen, G. L. (2006). The psychology of self-defense: Self-affirmation theory. In Zanna, M. P. (Ed.), Advances in experimental social psychology (Vol. 38, pp. 183–242). Academic Press.Google Scholar
Steele, C. M. (1988). The psychology of self-affirmation: Sustaining the integrity of the self. In Berkowitz, L. (Ed.), Advances in experimental social psychology (Vol. 21, pp. 261–302). Academic Press.Google Scholar
Steinfield, C., Ellison, N. B., & Lampe, C. (2008). Social capital, self-esteem, and use of online social network sites: A longitudinal analysis. Journal of Applied Developmental Psychology, 29, 434–445. doi: 10.1016/j.appdev.2008.07.002CrossRefGoogle Scholar
Suler, J. (2004). The online disinhibition effect. Cyberpsychology & Behavior, 7, 321–326. doi: 10.1089/1094931041291295CrossRefGoogle ScholarPubMed
Tandoc, E. C., Ferrucci, P., & Duffy, M. (2015). Facebook use, envy, and depression among college students: Is facebooking depressing? Computers in Human Behavior, 43, 139–146. http://dx.doi.org/10.1016/j.chb.2014.10.053CrossRefGoogle Scholar
Tiggemann, M., & Anderberg, I. (2019). Social media is not real: The effect of “Instagram vs reality” images on women’s social comparison and body image. New Media & Society. Advance online publication. doi: 10.1177/1461444819888720CrossRefGoogle Scholar
Toma, C. L. (2013). Feeling better but doing worse: Effects of Facebook self-presentation on implicit self-esteem and cognitive task performance. Media Psychology, 16(2), 199–220. https://doi.org/10.1080/15213269.2012.762189CrossRefGoogle Scholar
Toma, C. L., & Hancock, J. T. (2013). Self-affirmation underlies Facebook use. Personality and Social Psychology Bulletin, 39(3), 321–331. doi: 10.1177/0146167212474694CrossRefGoogle ScholarPubMed
Turkle, S. (2015). Reclaiming conversation: The power of talk in a digital age. Penguin Press.Google Scholar
Valkenburg, P. M. (2017). Understanding self-effects in social media. Human Communication Research, 43, 477–490. doi: 10.1111/hcre.12113CrossRefGoogle Scholar
Valkenburg, P. M., & Peter, J. (2007a). Internet communication and its relation to well-being: Identifying some underlying mechanisms. Media Psychology, 9(1), 43–58. doi: 10.1080/15213260709336802CrossRefGoogle Scholar
Valkenburg, P. M., & Peter, J. (2007b). Online communication and adolescent well-being: Testing the stimulation versus the displacement hypothesis. Journal of Computer-Mediated Communication, 12, 1169–1182. doi: 10.1111/j.1083-6101.2007.00368.xCrossRefGoogle Scholar
Valkenburg, P. M., & Peter, J. (2009). The effects of instant messaging on the quality of adolescents’ existing friendships: A longitudinal study. Journal of Communication, 59, 79–97. http://dx.doi.org/10.1111/j.1460-2466.2008.01405.xCrossRefGoogle Scholar
Valkenburg, P. M., & Peter, J. (2011). Online communication among adolescents: An integrated model of its attraction, opportunities, and risks. Journal of Adolescent Health, 48(2), 121–127. doi: 10.1016/j.jadohealth.2010.08.020.CrossRefGoogle ScholarPubMed
Verduyn, P., Lee, D. S., Park, J., Shablack, H., Orvell, A., Bayer, J., Ybarra, O., Jonides, J., & Kross, E. (2015). Passive Facebook usage undermines affective well-being: Experimental and longitudinal evidence. Journal of Experimental Psychology, 144(2), 480–488. http://dx.doi.org/10.1037/xge0000057CrossRefGoogle ScholarPubMed
Verduyn, P., Ybarra, O., Resibois, M., & Jonides, J., & Kross, E. (2017). Do social network sites enhance or undermine subjective well-being? A critical review. Social Issues and Policy Review, 11(1), 274–302. doi: 10.1111/sipr.12033CrossRefGoogle Scholar
Vogel, E., Rose, J., Okdie, B., & Eckles, K. (2015). Who compares and despairs? The effect of social comparison orientation on social media use and its outcomes. Personality and Individual Differences, 86, 249–256. doi: 10.1016/j.paid.2015.06.026CrossRefGoogle Scholar
Vogel, E. A., Rose, J. P., Roberts, L. R., & Eckles, K. (2014). Social comparison, social media, and self-esteem. Psychology of Popular Media Culture, 3(4), 206–222. doi: 10.1037/ppm0000047CrossRefGoogle Scholar
Wang, P., & Wang, X., Zhao, M., Wu, Y., Wang, Y., & Lei, L. (2019). Can social networking sites alleviate depression? The relation between authentic online self-presentation and adolescent depression: A mediation model of perceived social support and rumination. Current Psychology, 38, 1512–1521. https://doi.org/10.1007/s12144-017-9711-8CrossRefGoogle Scholar
Wang, R., Yang, F., & Haigh, M. M. (2017). Let me take a selfie: Exploring the psychological effects of posting and viewing selfies and groupies on social media. Telematics and Informatics, 34, 274–283. http://dx.doi.org/10.1016/j.tele.2016.07.004CrossRefGoogle Scholar
Weinstein, E. (2017). Adolescents’ differential responses to social media browsing: Exploring causes and consequences for intervention. Computers in Human Behavior, 76, 396–405. doi: 10.1016/j.chb.2017.07.038CrossRefGoogle Scholar
Wills, T. A. (1981). Downward comparison principles in social psychology. Psychological Bulletin, 90(2), 245. doi: 10.1037/0033-2909.90.2.245CrossRefGoogle Scholar
Wood, J. (1989). Theory and research concerning social comparisons of personal attributes. Psychological Bulletin, 106(2), 231–248. doi: 10.1037/0033-2909.106.2.231CrossRefGoogle Scholar
Yang, C.-c. (2016). Instagram use, loneliness, and social comparison orientation: Interact and browse on social media, but don’t compare. Cyberpsychology, Behavior, and Social Networking, 19(12), 703–708. doi: 10.1089/cyber.2016.0201CrossRefGoogle ScholarPubMed
Yang, C.-c., & Brown, B. B. (2013). Motives for using Facebook, patterns of Facebook activities, and late adolescents’ social adjustment to college. Journal of Youth and Adolescence, 42, 403–416. doi: 10.1007/s10964-012-9836-xCrossRefGoogle ScholarPubMed
Yang, C.-c., & Brown, B. B. (2016). Online self-presentation on Facebook and self-development during the college transition. Journal of Youth and Adolescence, 45(2), 402–416. doi: 10.1007/s10964-015-0385-yCrossRefGoogle ScholarPubMed
Yang, C.-c., & Christofferson, K. (2020). On the phone when we’re hanging out: Digital Social Multitasking (DSMT) and its socioemotional implications. Journal of Youth and Adolescence, 49, 1209–1224. https://doi.org/10.1007/s10964–020–01230–0CrossRefGoogle ScholarPubMed
Yang, C.-c, Holden, S. M., & Carter, M. D. K. (2017). Emerging adults’ social media self-presentation and identity development at college transition: Mindfulness as a moderator. Journal of Applied Developmental Psychology, 52, 212–221. doi: 10.1016/j.appdev.2017.08.006CrossRefGoogle Scholar
Yang, C.-c., Holden, S. M., & Carter, M. D. K. (2018). Social media social comparison of ability (but not opinion) predicts lower identity clarity: Identity processing style as a mediator. Journal of Youth and Adolescence, 47(10), 2114–2128. doi: 10.1007/s10964-017-0801-6CrossRefGoogle ScholarPubMed
Yang, C-c., Holden, S. M., & Carter, M. D. K., & Webb, J. J. (2018). Social media social comparison and identity distress at the college transition: A dual-path model. Journal of Adolescence, 69, 92–102. doi: https://doi.org/10.1016/j.adolescence.2018.09.007CrossRefGoogle ScholarPubMed
Yang, C.-c., & Lee, Y. (2020). Interactants and activities on Facebook, Instagram, and Twitter: Associations between social media use and social adjustment to college. Applied Developmental Science, 24(1), 62–78. doi: 10.1080/10888691.2018.1440233CrossRefGoogle Scholar
Yang, C.-c., & Robinson, A. (2018). Not necessarily detrimental: Two social comparison orientations and their associations with social media use and college social adjustment. Computers in Human Behavior, 84, 49–57. doi: 10.1016/j.chb.2018.02.020CrossRefGoogle Scholar
Zell, A. L., & Moeller, L. (2018). Are you happy for me … on Facebook? The potential importance of “likes” and comments. Computers in Human Behavior, 78, 26–33. http://dx.doi.org/10.1016/j.chb.2017.08.050CrossRefGoogle Scholar
Zhang, R. (2017). The stress-buffering effect of self-disclosure on Facebook: An examination of stressful life events, social support, and mental health among college students. Computers in Human Behavior, 75, 527–537. http://dx.doi.org/10.1016/j.chb.2017.05.043CrossRefGoogle Scholar