Linguistic analysis of differences in portrayal of movie characters

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pages 1669–1678 Vancouver, Canada, July 30 - August 4, 2017. c⃝2017 Association for Computational Linguistics https://doi.org/10.18653/v1/P17-1153 Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pages 1669–1678 Vancouver, Canada, July 30 - August 4, 2017. c⃝2017 Association for Computational Linguistics https://doi.org/10.18653/v1/P17-1153 Linguistic analysis of differences in portrayal of movie characters Anil Ramakrishna1, Victor R. Mart´ınez1, Nikolaos Malandrakis1, Karan Singla1, and Shrikanth Narayanan1,2 1Department of Computer Science 2Department of Electrical Engineering University of Southern California, Los Angeles, USA {akramakr, victorrm, malandra, singlak}@usc.edu, shri@sipi.usc.edu Abstract We examine differences in portrayal of characters in movies using psycholinguis- tic and graph theoretic measures computed directly from screenplays. Differences are examined with respect to characters’ gen- der, race, age and other metadata. Psy- cholinguistic metrics are extrapolated to dialogues in movies using a linear regres- sion model built on a set of manually anno- tated seed words. Interesting patterns are revealed about relationships between gen- ders of production team and the gender ra- tio of characters. Several correlations are noted between gender, race, age of charac- ters and the linguistic metrics. 1 Introduction Movies are often described as having the power to influence individual beliefs and values. In (Cape, 2003), the authors assert movies’ influence in both creating new thinking patterns in previously unex- plored social phenomena, especially in children, as well as their ability to update an individual’s ex- isting social boundaries based on what is shown on screen as the ”norm”. Some authors claim the in- verse (Wedding and Boyd, 1999): that movies re- flect existing cultural values of the society, adding weight to their ability in influencing individual be- liefs of what is accepted as the norm. As a result, they are studied in multiple disciplines to analyze their influence. Movies are particularly scrutinized in aspects involving negative stereotyping (Cape, 2003; Dimnik and Felton, 2006; Ter Bogt et al., 2010; Hedley, 1994) since this may introduce question- able beliefs in viewers. Negative stereotyping is believed to impact society in multiple aspects such as self-induced undermining of ability (Davies et al., 2005) as well as causing forms of prej- udice that can impact leadership or employment prospects (Eagly and Karau, 2002; Niven, 2006). Studies in analyzing stereotyping in movies typi- cally rely on collecting manual annotations on a small set of movies on which hypotheses tests are conducted (Behm-Morawitz and Mastro, 2008; Benshoff and Griffin, 2011; Hooks, 2009). In this work, we present large scale automated analyses of movie characters using language used in dialogs to study stereotyping along factors such as gender, race and age. Language use has been long known as a strong indicator of the speaker’s psychological and emo- tional state (Gottschalk and Gleser, 1969) and is well studied in a number of applications such as automatic personality detection (Mairesse et al., 2007) and psychotherapy (Xiao et al., 2015; Pen- nebaker et al., 2003). Computational analysis of language has been particularly popular thanks to advancements …

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