Although word and character n-grams have been used as features in different NLP applications, no systematic comparison or analysis has shown the power of character-based features for detecting abusive language. In this study, we investigate the effectiveness of such features for abusive language detection in user-generated online comments, and show that such methods outperform previous state-of-the-art approaches and other strong baselines.
CITATION STYLE
Mehdad, Y., & Tetreault, J. (2016). Do Characters Abuse More Than Words? In SIGDIAL 2016 - 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue, Proceedings of the Conference (pp. 299–303). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w16-3638
Mendeley helps you to discover research relevant for your work.