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dc.contributor.authorWester, Aksel Ladegård
dc.contributor.authorØvrelid, Lilja
dc.contributor.authorVelldal, Erik
dc.contributor.authorHammer, Hugo Lewi
dc.date.accessioned2017-01-25T10:37:10Z
dc.date.accessioned2017-03-16T09:18:49Z
dc.date.available2017-01-25T10:37:10Z
dc.date.available2017-03-16T09:18:49Z
dc.date.issued2016
dc.identifier.citationWester WA, Øvrelid L, Velldal E, Hammer HL: Threat detection in online discussions. In: Balahur A, van der Goot E, Vossen P, Montoyo A. Proceedings of the 7th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis WASSA@NAACL-HLT 2016 (WASSA 2016), 2016. Association for Computational Linguistics p. 66-71language
dc.identifier.urihttps://hdl.handle.net/10642/4287
dc.description.abstractThis 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 combina- tions of lexical features outperform the use of more complex syntactic and semantic features for this task.language
dc.titleThreat detection in online discussionslanguage
dc.typeChapter
dc.typePeer reviewedlanguage
dc.typeChapter
dc.date.updated2017-01-25T10:37:10Z
dc.description.versionacceptedVersionlanguage
dc.identifier.cristin1375546
dc.source.isbn978-1-941643-82-2


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