LT3 at SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (hatEval)

Nina Bauwelinck, Gilles Jacobs, Véronique Hoste, Els Lefever

Abstract
This paper describes our contribution to the SemEval-2019 Task 5 on the detection of hate speech against immigrants and women in Twitter (hatEval). We considered a supervised classification-based approach to detect hate speech in English tweets, which combines a variety of standard lexical and syntactic features with specific features for capturing offensive language. Our experimental results show good classification performance on the training data, but a considerable drop in recall on the held-out test set.
Anthology ID:
S19-2077
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
436–440
Language:
URL:
https://aclanthology.org/S19-2077
DOI:
10.18653/v1/S19-2077
Bibkey:
Cite (ACL):
Nina Bauwelinck, Gilles Jacobs, Véronique Hoste, and Els Lefever. 2019. LT3 at SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (hatEval). In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 436–440, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
LT3 at SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (hatEval) (Bauwelinck et al., SemEval 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/paclic-22-ingestion/S19-2077.pdf
PDF Search