TL;DR
This study analyzes gender bias in media narratives by examining a large dataset of tropes from TVTropes.org, revealing patterns of gendered content, its reception, and creator influence.
Contribution
It introduces an automated method to score genderedness in tropes and provides comprehensive analysis of gender bias across media and creator demographics.
Findings
Certain tropes are highly gendered and prevalent across media.
Gender bias correlates with the popularity of media works.
Creator gender influences the types of tropes used.
Abstract
Popular media reflects and reinforces societal biases through the use of tropes, which are narrative elements, such as archetypal characters and plot arcs, that occur frequently across media. In this paper, we specifically investigate gender bias within a large collection of tropes. To enable our study, we crawl tvtropes.org, an online user-created repository that contains 30K tropes associated with 1.9M examples of their occurrences across film, television, and literature. We automatically score the "genderedness" of each trope in our TVTROPES dataset, which enables an analysis of (1) highly-gendered topics within tropes, (2) the relationship between gender bias and popular reception, and (3) how the gender of a work's creator correlates with the types of tropes that they use.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
