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README.md
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license: mit
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---
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license: mit
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# Dataset of our EMNLP 2019 Paper (Multilingual and Multi-Aspect Hate Speech Analysis)
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For more details about our dataset, please check our paper:
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@inproceedings{ousidhoum-etal-multilingual-hate-speech-2019,
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title = "Multilingual and Multi-Aspect Hate Speech Analysis",
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author = "Ousidhoum, Nedjma
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and Lin, Zizheng
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and Zhang, Hongming
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and Song, Yangqiu
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and Yeung, Dit-Yan",
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booktitle = "Proceedings of EMNLP",
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year = "2019",
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publisher = "Association for Computational Linguistics",
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}
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(You can preview our paper on https://arxiv.org/pdf/1908.11049.pdf)
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## Clarification
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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.)
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## Taxonomy
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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*.
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## Dataset
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Our dataset is composed of three csv files sorted by language. They contain the tweets and the annotations described in our paper:
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the hostility type *(column: tweet sentiment)*
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hostility directness *(column: directness)*
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target attribute *(column: target)*
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target group *(column: group)*
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annotator's sentiment *(column: annotator sentiment)*.
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## Experiments
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To replicate our experiments, please see https://github.com/HKUST-KnowComp/MLMA_hate_speech/blob/master/README.md
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