  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.
