@inproceedings{bauwelinck-etal-2019-lt3,
title = "{LT}3 at {S}em{E}val-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in {T}witter (hat{E}val)",
author = "Bauwelinck, Nina and
Jacobs, Gilles and
Hoste, V{\'e}ronique and
Lefever, Els",
editor = "May, Jonathan and
Shutova, Ekaterina and
Herbelot, Aurelie and
Zhu, Xiaodan and
Apidianaki, Marianna and
Mohammad, Saif M.",
booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S19-2077",
doi = "10.18653/v1/S19-2077",
pages = "436--440",
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.",
}
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%0 Conference Proceedings
%T LT3 at SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (hatEval)
%A Bauwelinck, Nina
%A Jacobs, Gilles
%A Hoste, Véronique
%A Lefever, Els
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F bauwelinck-etal-2019-lt3
%X 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.
%R 10.18653/v1/S19-2077
%U https://aclanthology.org/S19-2077
%U https://doi.org/10.18653/v1/S19-2077
%P 436-440
Markdown (Informal)
[LT3 at SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (hatEval)](https://aclanthology.org/S19-2077) (Bauwelinck et al., SemEval 2019)
ACL