Multilingual and Multitarget Hate Speech Detection in Tweets

Patricia Chiril, Farah Benamara Zitoune, Véronique Moriceau, Marlène Coulomb-Gully, Abhishek Kumar


Abstract
Social media networks have become a space where users are free to relate their opinions and sentiments which may lead to a large spreading of hatred or abusive messages which have to be moderated. This paper proposes a supervised approach to hate speech detection from a multilingual perspective. We focus in particular on hateful messages towards two different targets (immigrants and women) in English tweets, as well as sexist messages in both English and French. Several models have been developed ranging from feature-engineering approaches to neural ones. Our experiments show very encouraging results on both languages.
Anthology ID:
2019.jeptalnrecital-court.21
Volume:
Actes de la Conférence sur le Traitement Automatique des Langues Naturelles (TALN) PFIA 2019. Volume II : Articles courts
Month:
7
Year:
2019
Address:
Toulouse, France
Venue:
JEP/TALN/RECITAL
SIG:
Publisher:
ATALA
Note:
Pages:
351–360
Language:
URL:
https://aclanthology.org/2019.jeptalnrecital-court.21
DOI:
Bibkey:
Cite (ACL):
Patricia Chiril, Farah Benamara Zitoune, Véronique Moriceau, Marlène Coulomb-Gully, and Abhishek Kumar. 2019. Multilingual and Multitarget Hate Speech Detection in Tweets. In Actes de la Conférence sur le Traitement Automatique des Langues Naturelles (TALN) PFIA 2019. Volume II : Articles courts, pages 351–360, Toulouse, France. ATALA.
Cite (Informal):
Multilingual and Multitarget Hate Speech Detection in Tweets (Chiril et al., JEP/TALN/RECITAL 2019)
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PDF:
https://aclanthology.org/2019.jeptalnrecital-court.21.pdf