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.

Exploiting emojis for abusive language detection

Urheber*in: Wiegand, Michael; Ruppenhofer, Josef

Attribution 4.0 International

0
/
0

Language
Englisch

Subject
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)
Stroudsburg, Pennsylvania : Association for Computational Linguistics
(when)
2021-04-21

URN
urn:nbn:de:bsz:mh39-104168
Last update
06.03.2025, 9:00 AM CET

Data provider

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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

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