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• W4200107780 abstract "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." @default.
• W4200107780 created "2021-12-31" @default.
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• W4200107780 date "2022-02-01" @default.
• W4200107780 modified "2023-10-14" @default.
• W4200107780 title "Gender bias, social bias, and representation in Bollywood and Hollywood" @default.
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• W4200107780 doi "https://doi.org/10.1016/j.patter.2021.100409" @default.
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