Konferenzbeitrag
Exploiting emojis for abusive language detection
We propose to use abusive emojis, such as the “middle finger” or “face vomiting”, as a proxy for learning a lexicon of abusive words. Since it represents extralinguistic information, a single emoji can co-occur with different forms of explicitly abusive utterances. We show that our approach generates a lexicon that offers the same performance in cross-domain classification of abusive microposts as the most advanced lexicon induction method. Such an approach, in contrast, is dependent on manually annotated seed words and expensive lexical resources for bootstrapping (e.g. WordNet). We demonstrate that the same emojis can also be effectively used in languages other than English. Finally, we also show that emojis can be exploited for classifying mentions of ambiguous words, such as “fuck” and “bitch”, into generally abusive and just profane usages.
- Language
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Englisch
- Subject
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Smiley
Beleidigung
Beschimpfung
Lexikon
Kontrastive Linguistik
Ambiguität
fuck
Social Media
Computerunterstützte Kommunikation
Graphisches Symbol
Sprache
- Event
-
Geistige Schöpfung
- (who)
-
Wiegand, Michael
Ruppenhofer, Josef
- Event
-
Veröffentlichung
- (who)
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Stroudsburg, Pennsylvania : Association for Computational Linguistics
- (when)
-
2021-04-21
- URN
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urn:nbn:de:bsz:mh39-104168
- Last update
-
06.03.2025, 9:00 AM CET
Data provider
Leibniz-Institut für Deutsche Sprache - Bibliothek. If you have any questions about the object, please contact the data provider.
Object type
- Konferenzbeitrag
Associated
- Wiegand, Michael
- Ruppenhofer, Josef
- Stroudsburg, Pennsylvania : Association for Computational Linguistics
Time of origin
- 2021-04-21