Multilingual and Multi-Aspect Hate Speech Analysis
Nedjma Ousidhoum, Zizheng Lin, Hongming Zhang, Yangqiu Song, Dit-Yan Yeung
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.- Anthology ID:
- D19-1474
- Volume:
- 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:
- November
- Year:
- 2019
- Address:
- Hong Kong, China
- Editors:
- Kentaro Inui, Jing Jiang, Vincent Ng, Xiaojun Wan
- Venues:
- EMNLP | IJCNLP
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4675–4684
- Language:
- URL:
- https://preview.aclanthology.org/remove-affiliations/D19-1474/
- DOI:
- 10.18653/v1/D19-1474
- Cite (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.
- Cite (Informal):
- Multilingual and Multi-Aspect Hate Speech Analysis (Ousidhoum et al., EMNLP-IJCNLP 2019)
- PDF:
- https://preview.aclanthology.org/remove-affiliations/D19-1474.pdf
- Code
- HKUST-KnowComp/MLMA_hate_speech
- Data
- MLMA Hate Speech