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Are These Comments Triggering? Predicting Triggers of Toxicity in Online Discussions




TekijätHind Almerekhi, Haewoon Kwak, Joni Salminen, Bernard J. Jansen

ToimittajaYennun Huang, Irwin King, Tie-Yan Liu, Maarten van Steen

Konferenssin vakiintunut nimiInternational World Wide Web Conference

KustantajaAssociation for Computing Machinery

Julkaisuvuosi2020

Kokoomateoksen nimiThe Web Conference 2020: Proceedings of The World Wide Web Conference WWW 2020

Aloitussivu3033

Lopetussivu3040

ISBN978-1-4503-7023-3

DOIhttps://doi.org/10.1145/3366423.3380074

Verkko-osoitehttps://doi.org/10.1145/3366423.3380074

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/50745995


Tiivistelmä
Understanding the causes or triggers of toxicity adds a new dimension to the prevention of toxic behavior in online discussions. In this research, we define toxicity triggers in online discussions as a non-toxic comment that lead to toxic replies. Then, we build a neural network-based prediction model for toxicity trigger. The prediction model incorporates text-based features and derived features from previous studies that pertain to shifts in sentiment, topic flow, and discussion context. Our findings show that triggers of toxicity contain identifiable features and that incorporating shift features with the discussion context can be detected with a ROC-AUC score of 0.87. We discuss implications for online communities and also possible further analysis of online toxicity and its root causes.C1 - Taipei, TaiwanC3 - Proceedings of The Web Conference 2020

Ladattava julkaisu

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Last updated on 2024-26-11 at 21:23