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Detecting derogatory compounds – an unsupervised approach

  • We examine the new task of detecting derogatory compounds (e.g. curry muncher). Derogatory compounds are much more difficult to detect than derogatory unigrams (e.g. idiot) since they are more sparsely represented in lexical resources previously found effective for this task (e.g. Wiktionary). We propose an unsupervised classification approach that incorporates linguistic properties of compounds. It mostly depends on a simple distributional representation. We compare our approach against previously established methods proposed for extracting derogatory unigrams.

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Metadaten
Author:Michael Wiegand, Maximilian Wolf, Josef Ruppenhofer
URN:urn:nbn:de:bsz:mh39-90185
URL:https://www.aclweb.org/anthology/N19-1211
ISBN:978-1-950737-13-0
Parent Title (English):The 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Proceedings of the Conference Vol. 1. Minneapolis, Minnesota, June 2 - June 7, 2019
Publisher:The Association for Computational Linguistics
Place of publication:Stroudsburg, PA, USA
Editor:Jill Burstein, Christy Doran, Thamar Solorio
Document Type:Conference Proceeding
Language:English
Year of first Publication:2019
Date of Publication (online):2019/07/03
Publicationstate:Veröffentlichungsversion
Reviewstate:Peer-Review
GND Keyword:Automatische Sprachanalyse; Kompositum <Wortbildung>; Schimpfwort
First Page:2076
Last Page:2081
DDC classes:400 Sprache / 400 Sprache, Linguistik
Open Access?:ja
Leibniz-Classification:Sprache, Linguistik
Linguistics-Classification:Computerlinguistik
Program areas:Pragmatik
Program areas:Digitale Sprachwissenschaft
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International