Gender bias, social bias, and representation in Bollywood and Hollywood

• Published in: Patterns (New York, N.Y.) N.Y.), 2022-02, Vol.3 (2), p.100409, Article 100409
• Main Authors: Khadilkar, Kunal, KhudaBukhsh, Ashiqur R., Mitchell, Tom M.
• Format: Article
• Language: English
• Subjects: Bollywood; gender bias; Hollywood; social bias
• ISSN: 2666-3899; 2666-3899
• DOI: 10.1016/j.patter.2021.100409

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. [Display omitted] •Applies cutting-edge natural language processing methods to movie subtitles•Considers 700 popular Bollywood movies spanning 70 years to analyze evolving trends•Tracks evolving biases toward gender, color, geographic region, and religion•Compares movies from Bollywood, Hollywood, and critically acclaimed world movies With an outreach in more than 90 countries, a market share of 2.1 billion dollars and a target audience of at least 1.2 billion people, Bollywood, also known as the Mumbai film industry, is a formidable entertainment force. While the number of lives Bollywood can potentially touch is massive, no comprehensive natural language processing (NLP) study on the evolution of social and gender biases in Bollywood dialogues exists. Our study, conducted on a substantial corpus of 700 popular Bollywood movie subtitles spanning 70 years, uncovers social biases along the lines of colorism, son preference, and geographic and religious representation. While our study focuses on movie subtitles, the same NLP tools might be used to rapidly analyze hundreds or thousands of books, magazine articles, radio transcripts, or social media posts. As early evidence of social impact, this work has triggered an initial conversation within the film community initiated by widespread international media attention. We present a comprehensive analysis of gender and social biases present in English subtitles of popular Bollywood movies, spanning 70 years, using cutting-edge nat