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1.
Patterns (N Y) ; 3(4): 100486, 2022 Apr 08.
Artigo em Inglês | MEDLINE | ID: mdl-35465228

RESUMO

[This corrects the article DOI: 10.1016/j.patter.2022.100442.][This corrects the article DOI: 10.1016/j.patter.2021.100409.].

2.
Patterns (N Y) ; 3(2): 100409, 2022 Feb 11.
Artigo em Inglês | MEDLINE | ID: mdl-35199062

RESUMO

We use a suite of cutting-edge natural language processing methods to quantify and characterize societal and gender biases in popular movie content. Our data set consists of English subtitles of popular movies from Bollywood-the Mumbai film industry-spanning 7 decades (700 movies). In addition, we include movies from Hollywood and movies nominated for the Academy Awards for contrastive purposes. Our findings indicate that while the overall portrayal of women has improved over time in popular movie dialogues from both Bollywood and Hollywood, modern films still exhibit considerable gender bias and are yet to achieve equal representation among genders. We also observe a strong bias favoring fair skin color in Bollywood content that occurred consistently across all time periods we considered. While our geographic representation analysis indicates improved inclusion over time for several Indian states, it also reveals a long-standing under-representation of many northeastern Indian states.

3.
Patterns (N Y) ; 3(2): 100442, 2022 Feb 11.
Artigo em Inglês | MEDLINE | ID: mdl-35201241

RESUMO

[This corrects the article DOI: 10.1016/j.patter.2021.100409.].

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