Using data science to understand the film industry’s gender gap

@article{Kagan2020UsingDS,
  title={Using data science to understand the film industry’s gender gap},
  author={Dima Kagan and Thomas Chesney and Michael Fire},
  journal={Palgrave Communications},
  year={2020},
  volume={6},
  pages={1-16}
}
  • Dima Kagan, Thomas Chesney, Michael Fire
  • Published 2020
  • Sociology, Computer Science, Physics
  • Palgrave Communications
  • Data science can offer answers to a wide range of social science questions. Here we turn attention to the portrayal of women in movies, an industry that has a significant influence on society, impacting such aspects of life as self-esteem and career choice. To this end, we fused data from the online movie database IMDb with a dataset of movie dialogue subtitles to create the largest available corpus of movie social networks (15,540 networks). Analyzing this data, we investigated gender bias in… CONTINUE READING

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