Key Female Characters in Film Have More to Talk About Besides Men: Automating the Bechdel Test

Agarwal, Akshay; Zheng, Jiehan; Kamath, Shruti V; Balasubramanian, Sriram; Dey, Shirin A

doi:10.3115/v1/n15-1084

Cited by 31 publications

(34 citation statements)

References 22 publications

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“…There exist various sets of high-level criteria to assess gender bias of character portrayal in fiction (Yehl, 2013;Romano, 2013;Powers, 2016). Agarwal et al (2015), in particular, automate the Bechdel test using social network features, finding that women are less central to the plot in movies that fail it. We compare our linguistic analysis of power and agency with the Bechdel test, demonstrating the need for more fine-grained analysis of how gender is depicted in movies.…”

Section: Related Workmentioning

confidence: 99%

Connotation Frames of Power and Agency in Modern Films

Sap¹,

Prasettio²,

Holtzman³

et al. 2017

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

123

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The framing of an action influences how we perceive its actor. We introduce connotation frames of power and agency, a pragmatic formalism organized using frame semantic representations, to model how different levels of power and agency are implicitly projected on actors through their actions. We use the new power and agency frames to measure the subtle, but prevalent, gender bias in the portrayal of modern film characters and provide insights that deviate from the well-known Bechdel test. Our contributions include an extended lexicon of connotation frames along with a web interface that provides a comprehensive analysis through the lens of connotation frames.

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Section: Related Workmentioning

confidence: 99%

Connotation Frames of Power and Agency in Modern Films

Sap¹,

Prasettio²,

Holtzman³

et al. 2017

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

123

View full text Add to dashboard Cite

show abstract

“…There has also been work on using NLP techniques to analyze gender differences in language use by men versus women (Mohammad and Yang, 2011;Bamman et al, 2012Bamman et al, , 2014Agarwal et al, 2015). Mohammad and Yang (2011) analyze the way gender affects the expression of emotions in the Enron corpus.…”

Section: Computational Approaches Towards Gender and Powermentioning

confidence: 99%

Dialog Structure Through the Lens of Gender, Gender Environment, and Power

Prabhakaran

Rambow

2017

dad

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Understanding how the social context of an interaction affects our dialog behavior is of great interest to social scientists who study human behavior, as well as to computer scientists who build automatic methods to infer those social contexts. In this paper, we study the interaction of power, gender, and dialog behavior in organizational interactions. In order to perform this study, we first construct the Gender Identified Enron Corpus of emails, in which we semi-automatically assign the gender of around 23,000 individuals who authored around 97,000 email messages in the Enron corpus. This corpus, which is made freely available, is orders of magnitude larger than previously existing gender identified corpora in the email domain. Next, we use this corpus to perform a largescale data-oriented study of the interplay of gender and manifestations of power. We argue that, in addition to one’s own gender, the “gender environment” of an interaction, i.e., the gender makeup of one’s interlocutors, also affects the way power is manifested in dialog. We focus especially on manifestations of power in the dialog structure — both, in a shallow sense that disregards the textual content of messages (e.g., how often do the participants contribute, how often do they get replies etc.), as well as the structure that is expressed within the textual content (e.g., who issues requests and how are they made, whose requests get responses etc.). We find that both gender and gender environment affect the ways power is manifested in dialog, resulting in patterns that reveal the underlying factors. Finally, we show the utility of gender information in the problem of automatically predicting the direction of power between pairs of participants in email interactions.

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“…Within natural language processing, computational literary analysis has mostly targeted works of fiction such as novels, plays, and screenplays. Examples include analyzing characters, their relationships, and emotional trajectories (Chaturvedi et al, 2017;Iyyer et al, 2016;Elsner, 2012), identifying enemies and allies (Nalisnick and Baird, 2013), villains or heroes (Bamman et al, 2014(Bamman et al, , 2013, measuring the memorability of quotes (Danescu-Niculescu-Mizil et al, 2012), characterizing gender representation in dialogue (Agarwal et al, 2015;Ramakrishna et al, 2015;Sap et al, 2017), identifying perpetrators in crime se-Turning Point Description 1. Opportunity Introductory event that occurs after the presentation of the setting and the background of the main characters.…”

Section: Introductionmentioning

confidence: 99%

Movie Plot Analysis via Turning Point Identification

Papalampidi¹,

Keller²,

Lapata³

2019

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conferen

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According to screenwriting theory, turning points (e.g., change of plans, major setback, climax) are crucial narrative moments within a screenplay: they define the plot structure, determine its progression and thematic units (e.g., setup, complications, aftermath). We propose the task of turning point identification in movies as a means of analyzing their narrative structure. We argue that turning points and the segmentation they provide can facilitate processing long, complex narratives, such as screenplays, for summarization and question answering. We introduce a dataset consisting of screenplays and plot synopses annotated with turning points and present an end-to-end neural network model that identifies turning points in plot synopses and projects them onto scenes in screenplays. Our model outperforms strong baselines based on state-of-the-art sentence representations and the expected position of turning points.Recently divorced Meg Altman and her 11-year-old daughter Sarah have just purchased a four-story brownstone on New York City. The house's previous owner installed an isolated room used to protect the house's occupants from intruders. On the night the two move into the home, it is broken by Junior, the previous owner's grandson; Burnham, an employee of the residence's security company; and Raoul; a ski mask-wearing gunman.

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Key Female Characters in Film Have More to Talk About Besides Men: Automating the Bechdel Test

Cited by 31 publications

References 22 publications

Connotation Frames of Power and Agency in Modern Films

Connotation Frames of Power and Agency in Modern Films

Dialog Structure Through the Lens of Gender, Gender Environment, and Power

Movie Plot Analysis via Turning Point Identification

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