@inproceedings{ousidhoum-etal-2019-multilingual,
title = "Multilingual and Multi-Aspect Hate Speech Analysis",
author = "Ousidhoum, Nedjma and
Lin, Zizheng and
Zhang, Hongming and
Song, Yangqiu and
Yeung, Dit-Yan",
editor = "Inui, Kentaro and
Jiang, Jing and
Ng, Vincent and
Wan, Xiaojun",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-1474",
doi = "10.18653/v1/D19-1474",
pages = "4675--4684",
abstract = "Current research on hate speech analysis is typically oriented towards monolingual and single classification tasks. In this paper, we present a new multilingual multi-aspect hate speech analysis dataset and use it to test the current state-of-the-art multilingual multitask learning approaches. We evaluate our dataset in various classification settings, then we discuss how to leverage our annotations in order to improve hate speech detection and classification in general.",
}
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<abstract>Current research on hate speech analysis is typically oriented towards monolingual and single classification tasks. In this paper, we present a new multilingual multi-aspect hate speech analysis dataset and use it to test the current state-of-the-art multilingual multitask learning approaches. We evaluate our dataset in various classification settings, then we discuss how to leverage our annotations in order to improve hate speech detection and classification in general.</abstract>
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%0 Conference Proceedings
%T Multilingual and Multi-Aspect Hate Speech Analysis
%A Ousidhoum, Nedjma
%A Lin, Zizheng
%A Zhang, Hongming
%A Song, Yangqiu
%A Yeung, Dit-Yan
%Y Inui, Kentaro
%Y Jiang, Jing
%Y Ng, Vincent
%Y Wan, Xiaojun
%S Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F ousidhoum-etal-2019-multilingual
%X Current research on hate speech analysis is typically oriented towards monolingual and single classification tasks. In this paper, we present a new multilingual multi-aspect hate speech analysis dataset and use it to test the current state-of-the-art multilingual multitask learning approaches. We evaluate our dataset in various classification settings, then we discuss how to leverage our annotations in order to improve hate speech detection and classification in general.
%R 10.18653/v1/D19-1474
%U https://aclanthology.org/D19-1474
%U https://doi.org/10.18653/v1/D19-1474
%P 4675-4684
Markdown (Informal)
[Multilingual and Multi-Aspect Hate Speech Analysis](https://aclanthology.org/D19-1474) (Ousidhoum et al., EMNLP-IJCNLP 2019)
ACL
- Nedjma Ousidhoum, Zizheng Lin, Hongming Zhang, Yangqiu Song, and Dit-Yan Yeung. 2019. Multilingual and Multi-Aspect Hate Speech Analysis. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 4675–4684, Hong Kong, China. Association for Computational Linguistics.