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Sunken ships and screaming banshees: metaphor and evaluation in film reviews

Published online by Cambridge University Press:  28 April 2021

MATTEO FUOLI Open the ORCID record for MATTEO FUOLI [Opens in a new window] ,
JEANNETTE LITTLEMORE  and
SARAH TURNER
MATTEO FUOLI
Affiliation:
Department of English Language and Linguistics School of English, Drama and Creative Studies University of Birmingham Frankland Building Edgbaston BirminghamB15 [email protected] [email protected]
JEANNETTE LITTLEMORE
Affiliation:
Department of English Language and Linguistics School of English, Drama and Creative Studies University of Birmingham Frankland Building Edgbaston BirminghamB15 [email protected] [email protected]
SARAH TURNER
Affiliation:
School of Humanities, Faculty of Arts and Humanities Coventry University George Eliot Building, Room 410 Priory Street CoventryCV1 [email protected]
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Abstract

It has been suggested that metaphor often performs some sort of evaluative function. However, there have been few empirical studies addressing this issue. Moreover, little is known about the extent to which a metaphor needs to be creative in order to perform an evaluative function, or whether there are differences according to the type of evaluation, such as its degree of explicitness and its polarity. In order to investigate these questions, 94 film reviews from the Internet Movie Database (IMDB) were annotated for creative and conventional metaphor, and for positive and negative, inscribed and invoked evaluation. Approximately half of the metaphors in our corpus were found to perform an evaluative function. Creative metaphors were significantly more likely to perform an evaluative function than conventional metaphors. Metaphorical evaluation was found to be significantly more negative than non-metaphorical evaluation. Both creative and conventional metaphors were used more frequently to perform inscribed evaluation than invoked evaluation. However, the tendency towards inscribed evaluation was stronger for conventional metaphors than for creative metaphors. From a theoretical perspective, these findings call into question fundamental assumptions about the role of metaphor in performing evaluation, such as the claim, made in the Systemic Functional Linguistics literature, that metaphor invariably ‘provokes’ attitudinal meanings. We have shown that it can do so, but that it does not always do so. The study also offers methodological contributions, by introducing a new protocol for the annotation of creative metaphors as well as detailed guidelines for coding evaluation at different levels of explicitness.

Keywords

creative metaphorinvoked evaluationAppraisal frameworkmanual corpus annotation
Type
Research Article
Information
English Language & Linguistics , Volume 26 , Issue 1 , March 2022 , pp. 75 - 103
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

Artstein, Ron & Poesio, Massimo. 2008. Inter-coder agreement for computational linguistics. Computational Linguistics 34(4), 555–96.CrossRefGoogle Scholar
Bastian, Brock. 2017. A social dimension to enjoyment of negative emotion in art reception. Behavioral and Brain Sciences 40. doi: 10.1017/S0140525X17001601CrossRefGoogle ScholarPubMed
Bednarek, Monika. 2006. Evaluation in media discourse: Analysis of a newspaper corpus. London: A&C Black.Google Scholar
Bednarek, Monika. 2009. Emotion talk and emotional talk: Cognitive and discursive perspectives. In Prishwa, Hanna (ed.), Language and social cognition: Expression of the social mind. Berlin: Mouton de Gruyter.Google Scholar
Bowdle, Brian F. & Gentner, Dedre. 2005. The career of metaphor. Psychological Review 112(1), 193–216.CrossRefGoogle ScholarPubMed
Byrt, Ted, Bishop, J. & Carlin, John B.. 1993. Bias, prevalence and kappa. Journal of Clinical Epidemiology 46(5), 423–9.CrossRefGoogle ScholarPubMed
Cacciari, C., Bolonini, N., Senna, I., Pellicciari, M. C., Miniussi, C. & Papagno, C.. 2011. Literal, fictive and metaphorical motion sentences preserve the motion component of the verb: A TMS study. Brain and Language 119, 149–57.CrossRefGoogle ScholarPubMed
Cameron, Lynne. 2003. Metaphor in educational discourse. London: Continuum.Google Scholar
Cardillo, Eileen R., Watson, Christine, Schmidt-Snoek, Gwenda L., Kranjec, Alexander & Chatterjee, Anjan. 2012. From novel to familiar: Tuning the brain for metaphors. Neuroimage 59, 3212–21.CrossRefGoogle ScholarPubMed
Di Eugenio, Barbara & Glass, Michael. 2004. The kappa statistic: A second look. Computational Linguistics 30(1), 95–101.CrossRefGoogle Scholar
Du Bois, John W. 2007. The stance triangle. In Englebretson, R. (ed.), Stancetaking in discourse: Subjectivity, evaluation, interaction, 139–82. Amsterdam: John Benjamins.CrossRefGoogle Scholar
Ellis, B. 1998. Opinion: What's race got to do with it? The Sydney Morning Herald, 6 June.Google Scholar
Fainsilber, Lynn & Ortony, Andrew. 1987. Metaphorical uses of language in the expression of emotions. Metaphor and Symbol 2(4), 239–50.CrossRefGoogle Scholar
Feinstein, Alvan R. & Cicchetti, Domenic V.. 1990. High agreement but low kappa: I. The problems of two paradoxes. Journal of Clinical Epidemiology 43(6), 543–9.CrossRefGoogle ScholarPubMed
Fuoli, Matteo. 2018. A stepwise method for annotating APPRAISAL. Functions of Language 25(2), 229–58.CrossRefGoogle Scholar
Gibbs, Raymond. 1994. The poetics of mind: Figurative thought, language, and understanding. Cambridge: Cambridge University Press.Google Scholar
Gibbs, Raymond W. Jr & Franks, Heather. 2002. Embodied metaphor in women's narratives about their experiences with cancer. Health Communication 14(2), 139–65.CrossRefGoogle ScholarPubMed
Hanks, Patrick. 2006. Metaphoricity is gradable. In Stefanowitsch, Anatol & Th, Stefan. Gries (eds.), Corpora in cognitive linguistics, vol.1: Metaphor and metonymy. Berlin and New York: Mouton de Gruyter.Google Scholar
Hood, Susan & Martin, James R.. 2005. Invoking attitude: The play of graduation in appraising discourse. Revista Signos 38 (58), pp. 195–220.Google Scholar
Hunston, Susan. 2011. Corpus approaches to evaluation: Phraseology and evaluative language. Abingdon: Routledge.Google Scholar
Hunston, Susan & Thompson, Geoff. 2000. Evaluation in text: Authorial stance and the construction of discourse. Oxford: Oxford University Press.Google Scholar
Lakoff, George & Johnson, Mark. 1980. Metaphors we live by. Chicago: University of Chicago Press.Google Scholar
Landis, J. Richard & Koch, Gary G.. 1977. An application of hierarchical kappa-type statistics in the assessment of majority agreement among multiple observers. Biometrics, 363–74.CrossRefGoogle ScholarPubMed
Littlemore, Jeannette. 2019. Metaphors in the mind: Sources of variation in embodied metaphor. New York: Cambridge University Press.CrossRefGoogle Scholar
Liu, Feifei. 2018. Lexical metaphor as affiliative bond in newspaper editorials: A systemic functional linguistics perspective. Functional Linguistics 5(1), 2.CrossRefGoogle Scholar
Martin, J. R. 2020. Metaphors we feel by: Stratal tension. Journal of World Languages 6(1–2), 8–26.CrossRefGoogle Scholar
Martin, J. R & White, P. R. R.. 2005. The language of evaluation: Appraisal in English. Basingstoke: Palgrave Macmillan.CrossRefGoogle Scholar
Moon, Rosamund. 1998. Fixed expressions and idioms in English: A corpus-based approach. Oxford: Clarendon Press.Google Scholar
Pang, Bo & Lee, Lillian. 2004. A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. ArXiv:Cs/0409058. http://arxiv.org/abs/cs/0409058CrossRefGoogle Scholar
Pragglejaz Group. 2007. MIP: A method for identifying metaphorically used words in discourse. Metaphor and Symbol 22(1), 1–39. https://doi.org/10.1080/10926480709336752CrossRefGoogle Scholar
QSR International Pty Ltd. 2020. NVivo Qualitative Data Analysis Software [software]. www.qsrinternational.com/nvivo-qualitative-data-analysis-software/homeGoogle Scholar
Rozin, Paul & Royzman, Edward B.. 2001. Negativity bias, negativity dominance, and contagion. Personality and Social Psychology Review 5(4), 296–320.CrossRefGoogle Scholar
Sakamoto, Maki & Utsumi, Akira. 2014. Adjective metaphors evoke negative meanings. PLOS ONE 9(2), e89008. https://doi.org/10.1371/journal.pone.0089008CrossRefGoogle ScholarPubMed
Schubert, Emery. 1996. Enjoyment of negative emotions in music: An associative network explanation. Psychology of Music 24(1), 18–28.CrossRefGoogle Scholar
Semino, Elena. 2008. Metaphor in discourse. Cambridge: Cambridge University Press.Google Scholar
Simon-Vandenbergen, Anne-Marie, Taverniers, Miriam & Ravelli, Louise J.. 2003. Grammatical metaphor: Views from systemic functional linguistics. Amsterdam: John Benjamins.CrossRefGoogle Scholar
Steen, Gerald J. S., Dorst, Aletta G., Berenike Herrmann, J., Kaal, Anna A., Krennmayr, Tina & Pasma, Trijntje. 2010. A method for linguistic metaphor identification: From MIP to MIPVU. Amsterdam: John Benjamins.CrossRefGoogle Scholar
Taboada, Maite. 2011. Stages in an online review genre. Text & Talk 31(2), 247–69.CrossRefGoogle Scholar
Turner, Sarah L. 2014. The development of metaphoric competence in French and Japanese learners of English. PhD thesis, University of Birmingham.Google Scholar
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