Analyzing Gender Bias within Narrative Tropes
October 30, 2020 ยท Declared Dead ยท ๐ NLPCSS
"No code URL or promise found in abstract"
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Authors
Dhruvil Gala, Mohammad Omar Khursheed, Hannah Lerner, Brendan O'Connor, Mohit Iyyer
arXiv ID
2011.00092
Category
cs.CL: Computation & Language
Citations
16
Venue
NLPCSS
Last Checked
4 months ago
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.
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