Identifying Missing Component in the Bechdel Test Using Principal Component Analysis Method
Raghav Lakhotia, Chandra Kanth Nagesh, Krishna Madgula

TL;DR
This study applies Principal Component Analysis to movie scripts to identify additional parameters influencing female representation, suggesting that female dialogue content is a crucial factor often overlooked in the traditional Bechdel Test.
Contribution
The paper introduces new parameters for assessing female representation in films and demonstrates their significance using PCA on a large dataset of movie scripts.
Findings
Female dialogue content is a key component in representation.
Additional parameters improve the assessment of female presence.
PCA reveals the importance of dialogue content over traditional criteria.
Abstract
A lot has been said and discussed regarding the rationale and significance of the Bechdel Score. It became a digital sensation in 2013 when Swedish cinemas began to showcase the Bechdel test score of a film alongside its rating. The test has drawn criticism from experts and the film fraternity regarding its use to rate the female presence in a movie. The pundits believe that the score is too simplified and the underlying criteria of a film to pass the test must include 1) at least two women, 2) who have at least one dialogue, 3) about something other than a man, is egregious. In this research, we have considered a few more parameters which highlight how we represent females in film, like the number of female dialogues in a movie, dialogue genre, and part of speech tags in the dialogue. The parameters were missing in the existing criteria to calculate the Bechdel score. The research aims…
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Taxonomy
TopicsSentiment Analysis and Opinion Mining · Music and Audio Processing · Advanced Text Analysis Techniques
