license: mit
Disclaimer
This is a hate speech dataset (in Arabic, French, and English).
Offensive content that does not reflect the opinions of the authors.
Dataset of our EMNLP 2019 Paper (Multilingual and Multi-Aspect Hate Speech Analysis)
For more details about our dataset, please check our paper:
@inproceedings{ousidhoum-etal-multilingual-hate-speech-2019,
title = "Multilingual and Multi-Aspect Hate Speech Analysis",
author = "Ousidhoum, Nedjma
and Lin, Zizheng
and Zhang, Hongming
and Song, Yangqiu
and Yeung, Dit-Yan",
booktitle = "Proceedings of EMNLP",
year = "2019",
publisher = "Association for Computational Linguistics",
}
(You can preview our paper on https://arxiv.org/pdf/1908.11049.pdf)
Clarification
The multi-labelled tasks are the hostility type of the tweet and the annotator's sentiment. (We kept labels on which at least two annotators agreed.)
Taxonomy
In further experiments that involved binary classification tasks of the hostility/hate/abuse type, we considered single-labelled normal instances to be non-hate/non-toxic and all the other instances to be toxic.
Dataset
Our dataset is composed of three csv files sorted by language. They contain the tweets and the annotations described in our paper:
the hostility type (column: tweet sentiment)
hostility directness (column: directness)
target attribute (column: target)
target group (column: group)
annotator's sentiment (column: annotator sentiment).
Experiments
To replicate our experiments, please see https://github.com/HKUST-KnowComp/MLMA_hate_speech/blob/master/README.md