Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-26T17:10:45.580Z Has data issue: false hasContentIssue false
  • English
  • Français

#polisci Twitter: A Descriptive Analysis of how Political Scientists Use Twitter in 2019

Published online by Cambridge University Press:  23 December 2020

James Bisbee Open the ORCID record for James Bisbee [Opens in a new window] ,
Jennifer Larson  and
Kevin Munger
Get access Rights & Permissions [Opens in a new window]

Abstract

Knowledge creation is a social enterprise, especially in political science. Sharing new findings widely and quickly is essential for progress. Scholars can now use Twitter to rapidly disseminate ideas, and many do. What are the implications of this new tool? Who uses it, how do they use it, and what are the implications for exacerbating or ameliorating existing inequalities in terms of research dissemination and attention? We construct a novel dataset of all 1,236 political science professors at PhD-granting institutions in the United States who have a Twitter account to answer these questions. We find that female scholars and those on the tenure track are more likely to use Twitter, especially for the dissemination of research. However, we consistently find that research by men shared on Twitter is more likely to be passed along further by men than research by women.

Type
Article
Information
Perspectives on Politics , Volume 20 , Issue 3 , September 2022 , pp. 879 - 900
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of the American Political Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

A list of permanent links to Supplemental Materials provided by the authors precedes the References section.

*Data replication sets are available in Harvard Dataverse at: https://doi.org/10.7910/DVN/SUBWTT

References

Aronow, Peter M, Samii, Cyrus, and Assenova, Valentina A. 2015. “Cluster-Robust Variance Estimation for Dyadic Data.” Political Analysis 23(4): 564-77.CrossRefGoogle Scholar
Atkeson, Lonna Rae, and Taylor, Andrew J. 2019. “Partisan Affiliation in Political Science: Insights from Florida and North Carolina.” PS: Political Science & Politics 52(4): 706-10.Google Scholar
Barberá, Pablo. 2015. “Birds of the Same Feather Tweet Together. Bayesian Ideal Point Estimation Using Twitter Data.” Political Analysis 23(1): 76-91.CrossRefGoogle Scholar
Barnes, Tiffany D., and Beaulieu, Emily. 2017. “Engaging Women: Addressing the Gender Gap in Women's Networking and Productivity.” PS: Political Science & Politics 50(2): 461-66.Google Scholar
Beaulieu, Emily, Boydstun, Amber E, Brown, Nadia E, Dionne, Kim Yi, Gillespie, Andra, Klar, Samara, Krupnikov, Yanna, Michelson, Melissa R, Searles, Kathleen, and Wolbrecht, Christina. 2017. “Women Also Know Stuff: Meta-Level Mentoring to Battle Gender Bias in Political Science.” PS: Political Science & Politics 50(3): 779-83.Google Scholar
Bisbee, James, Dehejia, Rajeev, Pop-Eleches, Cristian, and Samii, Cyrus. 2017. “Local Instruments, Global Extrapolation: External Validity of the Labor Supply-Fertility Local Average Treatment Effect.” Journal of Labor Economics 35(S1): S99-47.CrossRefGoogle Scholar
Breuning, Marijke, Gross, Benjamin Isaak, Feinberg, Ayal, Martinez, Melissa, Sharma, Ramesh, and Ishiyama, John. 2018. “Clearing the Pipeline? Gender and the Review Process at the American Political Science Review .” PS: Political Science & Politics 51(3): 629-34.Google Scholar
Dion, Michelle L., Sumner, Jane Lawrence, and Mitchell, Sara McLaughlin. 2018. “Gendered Citation Patterns across Political Science and Social Science Methodology Fields.” Political Analysis 26(3): 312-27.Google Scholar
Esarey, Justin, and Bryant, Kristin. 2018. “Are Papers Written by Women Authors Cited Less Frequently?” Political Analysis 26(3): 331-34.CrossRefGoogle Scholar
Eysenbach, Gunther. 2011. “Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact.” Journal of medical Internet research 13(4) e123.Google ScholarPubMed
Flaherty, Colleen. 2018. “A Non-Tenure Track Profession?” Inside HigherEd, October 12. (https://www.insidehighered.com/news/2018/10/12/about-three-quarters-all-faculty-positions-are-tenure-track-according-new-aaup).Google Scholar
Gerring, John. 2012. “Mere Description.” British Journal of Political Science 42(4): 721-46.CrossRefGoogle Scholar
Gray, , Phillip, W. N.d. “Diagnosis versus Ideological Diversity.” PS: Political Science & Politics. Forthcoming.Google Scholar
Hindman, Matthew. 2008. The Myth of Digital Democracy. Princeton, NJ: Princeton University Press.Google Scholar
Jaidka, Kokil, Zhou, Alvin, and Lelkes, Yphtach. 2018. “Brevity Is the Ssoul of Twitter: The Constraint Affordance and Political Discussion.” Journal of Communication 69(4): 345-72.CrossRefGoogle Scholar
Ke, Qing, Ahn, Yong-Yeol, and Sugimoto, Cassidy R. 2017. “A Systematic Identification and Analysis of Scientists on Twitter.” PLoS One 12(4): e0175368. https://doi.org/10.1371/journal.pone.0175368 Google ScholarPubMed
Key, Ellen M., and Sumner, Jane Lawrence. 2018. “You Research Like a Girl: Gendered Research Agendas and Their Implications.” PS: Political Science & Politics 52(4): 663-68.Google Scholar
Kim, Hannah June, and Grofman, Bernard. 2019. “The Political Science 400: With Citation Counts by Cohort, Gender, and Subfield.” PS: Political Science & Politics 52(2): 296-311.Google Scholar
Klar, Samara, Krupnikov, Yanna, Ryan, John Barry, Searles, Kathleen, and Shmargad, Yotam. 2020. “Using Social Media to Promote Academic Research: Identifying the Benefits of Twitter for Sharing Academic Work.” PloS one 15(4): e0229446. https://doi.org/10.1371/journal.pone.0229446 Google ScholarPubMed
Kreiss, Daniel. 2016. “Seizing the Moment: The Presidential Campaigns' Use of Twitter during the 2012 Electoral Cycle.” New Media & Society 18(8): 1473-90.Google Scholar
Marwick, Alice E., and Boyd, Danah. 2011. “I Tweet Honestly, I Tweet Passionately: Twitter Users, Context Collapse, and the Imagined Audience.” New Media & Society 13(1): 114-33.CrossRefGoogle Scholar
Mohammadi, Ehsan, Thelwall, Mike, Kwasny, Mary, and Holmes, Kristi L. 2018. “Academic Information on Twitter: A User Survey.” PloS one 13(5): e0197265.CrossRefGoogle ScholarPubMed
Mourao, Rachel Reis. 2015. “The Boys on the Timeline: Political Journalists' Use of Twitter for Building Interpretive Communities.” Journalism 16(8): 1107-23.CrossRefGoogle Scholar
Munger, Kevin. 2017. “Tweetment Effects on the Tweeted: Experimentally Reducing Racist Harassment.” Political Behavior 39(3): 629-49.CrossRefGoogle Scholar
Munger, Kevin. 2019. “The Limited Value of Non-Replicable Field Experiments in Contexts with Low Temporal Validity.” Social Media + Society 5(3). https://doi.org/10.1177%2F2056305119859294 CrossRefGoogle Scholar
Ortega, Jose Luis. 2016. “To Be or Not to Be on Twitter, and Its Relationship with the Tweeting and Citation of Research Papers.” Scientometrics 109(2): 1353-64.CrossRefGoogle Scholar
Peoples, Brandon K., Midway, Stephen R., Sackett, Dana, Lynch, Abigail, and Cooney, Patrick B.. 2016. “Twitter Predicts Citation Rates of Ecological Research.” PloS one 11(11): e0166570.CrossRefGoogle ScholarPubMed
Raghavan, Usha Nandini, Albert, Reka, and Kumara, Soundar. 2007. “Near Linear Time Algorithm to Detect Community Structures in Large-Scale Networks.” Physical Review E 76(3): 036106.CrossRefGoogle ScholarPubMed
Rom, , , Mark Carl. 2019. “A Liberal Polity: Ideological Homogeneity in Political Science.” PS: Political Science & Politics 52(4): 701-705.Google Scholar
Searles, Kathleen, and Krupnikov, Yanna. 2018. “How Not to Get Ratioed and Other Advice for the Savvy Graduate Mentor.” Political Communication 35(4):669-73.CrossRefGoogle Scholar
Sen, Maya. 2018. “Response to Dion, Sumner, and Mitchell.” Political Analysis 26(3): 335-37.CrossRefGoogle Scholar
Shen, Jieli, Liu, Regina Y, and Xie, Min-ge. 2018. “Prediction with Confidence—A General Framework for Predictive Inference.” Journal of Statistical Planning and Inference 195: 126-40.CrossRefGoogle Scholar
Tufekci, Zeynep. 2014. “Big Questions for Social Media Big Data: Representativeness, Validity and Other Methodological Pitfalls.” In Eighth International AAAI Conference on Weblogs and Social Media. Google Scholar
Usher, Nikki, Holcomb, Jesse, and Littman, Justin. 2018. “Twitter Makes It Worse: Political Journalists, Gendered Echo Chambers, and the Amplification of Gender Bias.” International Journal of Press/Politics 23(3): 324-44.CrossRefGoogle Scholar
U.S. News & World Report . 2019. “U.S. News Education Rankings Colleges.” (https://www.usnews.com/best-colleges/rankings)Google Scholar
Wilson, , , J. Matthew. N.d. “The Nature and Consequences of Ideological Hegemony in American Political Science.” PS: Political Science & Politics 52(4): 724-27.Google Scholar
Yi Dionne, , , Kim. 2019. “There’s a Gender Gap in Political Science. Our Series Examines the Problem—and Looks at Some Solutions.” Washington Post: Monkey Cage, August 19. (https://www.washingtonpost.com/politics/2019/08/19/theres-gender-gap-political-science-our-series-examines-problem-looks-some-solutions/)Google Scholar
Supplementary material: PDF

Bisbee et al. supplementary material

Bisbee et al. supplementary material

Download Bisbee et al. supplementary material(PDF)
PDF 1.4 MB
Supplementary material: Link

Bisbee et al. Dataset

Dataset

https://doi.org/10.7910/DVN/SUBWTT
Link