''Shut Up and Let Me Enjoy My Otome': Understanding and Measuring the Toxicity in Otome Game Communities
Yage Zhang, Xinyue Shen, Yukun Jiang, Michael Backes, Yang Zhang
Abstract
Otome games, a romance simulation genre primarily targeting female, have emerged as a major force in the global gaming market, attracting hundreds of millions of players and billions in revenue. Despite their popularity, otome game communities face pervasive online toxicity, which has been largely unexplored. In this work, we present the first largescale measurement of toxicity in otome game communities across social platforms. We introduce OtomeSCAN, a framework for collecting, evaluating, and analyzing 620,045 posts from Weibo and Reddit spanning 18 months. To support robust analysis, we manually annotated a ground-truth dataset of 4,308 posts, identifying eight target groups such as players and game developers. We evaluate seven toxicity detectors on the dataset, including general-purpose models and our proposed LLM-based detectors, with our best model achieving F1-scores of 0.82 (Weibo) and 0.78 (Reddit). Our analysis reveals significant platform-based differences in toxicity: 22.20% of otome-related posts on Weibo are toxic, compared to 3.71% on Reddit. Besides, real-world events like in-community conflicts can rapidly escalate toxicity, with toxicity ratios increasing to 37.09% in just 72 hours during an external attack on Weibo. We also flag 191 potentialcoordination clusters in otome game communities, 64.40% of which target game developers, with several accounts participating repeatedly across multiple clusters. We hope our work inspires further research on community-specific toxicity and contributes to building healthier online spaces for marginalized gaming communities. 1 Disclaimer: This paper contains examples of toxic and abusive language. Reader discretion is recommended.
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