TY - GEN
T1 - Are These Comments Triggering? Predicting Triggers of Toxicity in Online Discussions
AU - Almerekhi, Hind
AU - Kwak, Haewoon
AU - Salminen, Joni
AU - Jansen, Bernard J.
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/4/20
Y1 - 2020/4/20
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85086570746&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85086570746&partnerID=8YFLogxK
U2 - 10.1145/3366423.3380074
DO - 10.1145/3366423.3380074
M3 - Conference contribution
AN - SCOPUS:85086570746
T3 - The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020
SP - 3033
EP - 3040
BT - The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020
PB - Association for Computing Machinery, Inc
T2 - 29th International World Wide Web Conference, WWW 2020
Y2 - 20 April 2020 through 24 April 2020
ER -