Abstract
This paper investigates the effect of various types of linguistic features (lexical, syntactic and semantic) for training classifiers to detect threats of violence in a corpus of YouTube comments. Our results show that combinations of lexical features outperform the use of more complex syntactic and semantic features for this task.
Cite
CITATION STYLE
Wester, A., Øvrelid, L., Velldal, E., & Hammer, H. L. (2016). Threat detection in online discussions. In Proceedings of the 7th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2016 at the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2016 (pp. 66–71). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w16-0413
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