Reproduce “Harassment on TikTok: A Mixed-Methods Analysis of Video Content and Psycholinguistic Comment Stances” on OpenResearch
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About this paper
Afsaneh Razi, Tyler Chang, Michal Monselise, Joseph J. Trybala, Asta Zelenkauskaite
The authors examine 190 TikTok videos tagged #harassment and their comments, combining manual video coding, LIWC analysis, and stance classification. Sexual harassment was the most frequent distinct category, while verbal-harassment videos had the highest average views (1,048,395). Comments were mostly neutral, and stance varied substantially across videos, so these observational hashtag-sample findings do not show that harassment type determines responses.
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