Abstract
The representation of gender stereotypes in films profoundly impacts societal values and beliefs since they reflect and can potentially reinforce prevailing social norms. Hence, it is crucial to unravel how such stereotypes arise from gender portrayal in films. In this paper, we decompose the gender differences portrayed in movies along several socio- and psycho-linguistic dimensions. In particular, we consider gender disparities in four dialogue dimensions: 1) the degree of assertion, 2) the degree of confirmation, 3) the valence of emotions, and 4) the topic. Empirical analyses show that the valence of emotions expressed in the dialogue explains the most variation in gender disparity. Moreover, for certain kinds of dialogue, such as those occurring between different gender actors, the topic of discussion is also a strong predictor of gender differences.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
We compute the gender ladenness scores using only the 274,596 words in the lexicon and dropped out-of-vocabulary words. We also removed stopwords as well as words that occurred less than 50 times in the movie scripts.
References
Angrist, J.D., Pischke, J.S.: Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton University Press (2008)
Cape, G.S.: Addiction, stigma and movies. Acta Psychiatrica Scandinavica 107(3), 163–169 (2003)
Carli, L.L.: Gender, language, and influence. J. Pers. Soc. Psychol. 59(5), 941–951 (1990)
Clark, J.M., Paivio, A.: Extensions of the paivio, yuille, and madigan (1968) norms. Behav. Res. Methods Instrum. Comput. 36(3), 371–383 (2004)
Danescu-Niculescu-Mizil, C., Lee, L.: Chameleons in imagined conversations: a new approach to understanding coordination of linguistic style in dialogs. arXiv preprint arXiv:1106.3077 (2011)
Dhillon, P.S., Talukdar, P.P., Crammer, K.: Inference-driven metric learning for graph construction. In: 4th North East Student Colloquium on Artificial Intelligence (2010)
Feng, D., O’Halloran, K.L.: The multimodal representation of emotion in film: integrating cognitive and semiotic approaches. Semiotica 2013(197), 79–100 (2013)
Fitzpatrick, M.A., Mulac, A., Dindia, K.: Gender-preferential language use in spouse and stranger interaction. J. Lang. Soc. Psychol. 14(1–2), 18–39 (1995)
Holmes, J.: Women, language and identity. Journal of Sociolinguistics 1(2), 195–223 (1997). https://onlinelibrary.wiley.com/doi/abs/10.1111/1467-9481.00012, eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/1467-9481.00012
Holtzman, L.: Media Messages: What Film, Television, and Popular Music Teach Us About Race, Class, Gender, and Sexual Orientation. Routledge, 2 edn. (2014). https://doi.org/10.4324/9781315702469, https://www.taylorfrancis.com/books/9781315702469
Kagan, D., Chesney, T., Fire, M.: Using data science to understand the film industry’s gender gap. Palgrave Commun. 6(1), 1–16 (2020)
Kollock, P., Schwartz, P., Blumstein, P., Blumstein, P.: Sex and power in interaction: conversational privileges and duties. Am. Soc. Rev. 50, 34–46 (1985)
Lakoff, R.T.: Language and Woman’s Place: Text and Commentaries. Oxford University Press (2004)
Leaper, C., Ayres, M.M.: A meta-analytic review of gender variations in adults’ language use: talkativeness, affiliative speech, and assertive speech. Pers. Soc. Psychol. Rev. 11(4), 328–363 (2007). https://doi.org/10.1177/1088868307302221
Leaper, C., Robnett, R.D.: Women are more likely than men to use tentative language, aren’t they? a meta-analysis testing for gender differences and moderators. Psychol. Women Quart. 35(1), 129–142 (2011)
Malandrakis, N., Narayanan, S.S.: Therapy language analysis using automatically generated psycholinguistic norms. In: Sixteenth Annual Conference of the International Speech Communication Association (2015)
Newman, M.L., Groom, C.J., Handelman, L.D., Pennebaker, J.W.: Gender differences in language use: an analysis of 14,000 text samples. Discourse Process. 45(3), 211–236 (2008)
Ramakrishna, A., Martínez, V.R., Malandrakis, N., Singla, K., Narayanan, S.: Linguistic analysis of differences in portrayal of movie characters. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1669–1678 (2017)
Sap, M., Prasettio, M.C., Holtzman, A., Rashkin, H., Choi, Y.: Connotation frames of power and agency in modern films. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 2329–2334 (2017)
Schofield, A., Mehr, L.: Gender-distinguishing features in film dialogue. In: Proceedings of the Fifth Workshop on Computational Linguistics for Literature, pp. 32–39 (2016)
Talbot, M.: Gender stereotypes: reproduction and challenge. In: Holmes, J., Meyerhoff, M. (eds.) The Handbook of Language and Gender, pp. 468–486. Blackwell Publishing Ltd, Oxford, UK (2003). https://doi.org/10.1002/9780470756942.ch20
Tan, E.S.: Emotion and the Structure of Narrative Film: Film As An Emotion Machine. Routledge (2013). Google-Books-ID: 5khUAQAAQBAJ
Tausczik, Y.R., Pennebaker, J.W.: The psychological meaning of words: LIWC and computerized text analysis methods. J. Lang. Soc. Psychol. 29(1), 24–54 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Yu, Y., Hao, Y., Dhillon, P. (2022). Unpacking Gender Stereotypes in Film Dialogue. In: Hopfgartner, F., Jaidka, K., Mayr, P., Jose, J., Breitsohl, J. (eds) Social Informatics. SocInfo 2022. Lecture Notes in Computer Science, vol 13618. Springer, Cham. https://doi.org/10.1007/978-3-031-19097-1_26
Download citation
DOI: https://doi.org/10.1007/978-3-031-19097-1_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-19096-4
Online ISBN: 978-3-031-19097-1
eBook Packages: Computer ScienceComputer Science (R0)