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--- |
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license: unknown |
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language: |
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- fr |
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--- |
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### FrenchHateSpeechSuperset |
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This dataset is a superset of multiple datasets including hate speech, harasment, sexist, racist, etc...messages from various platforms. |
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Included datasets : |
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- MLMA dataset |
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- CAA dataset |
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- FTR dataset |
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- "An Annotated Corpus for Sexism Detection in French Tweets" dataset |
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- UC-Berkeley-Measuring-Hate-Speech dataset (translated from english*) |
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#### References |
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``` |
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@inproceedings{chiril2020annotated, |
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title={An Annotated Corpus for Sexism Detection in French Tweets}, |
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author={Chiril, Patricia and Moriceau, V{\'e}ronique and Benamara, Farah and Mari, Alda and Origgi, Gloria and Coulomb-Gully, Marl{\`e}ne}, |
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booktitle={Proceedings of The 12th Language Resources and Evaluation Conference}, |
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pages={1397--1403}, |
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year={2020} |
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} |
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``` |
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``` |
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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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``` |
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``` |
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Vanetik, N.; Mimoun, E. Detection of Racist Language in French Tweets. Information 2022, 13, 318. https://doi.org/10.3390/info13070318 |
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``` |
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``` |
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@article{kennedy2020constructing, |
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title={Constructing interval variables via faceted Rasch measurement and multitask deep learning: a hate speech application}, |
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author={Kennedy, Chris J and Bacon, Geoff and Sahn, Alexander and von Vacano, Claudia}, |
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journal={arXiv preprint arXiv:2009.10277}, |
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year={2020} |
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} |
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``` |
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``` |
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Anaïs Ollagnier, Elena Cabrio, Serena Villata, Catherine Blaya. CyberAgressionAdo-v1: a Dataset of Annotated Online Aggressions in French Collected through a Role-playing Game. Language Resources and Evaluation Conference, Jun 2022, Marseille, France. ⟨hal-03765860⟩ |
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``` |
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### Translation |
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French datasets for hate speech are quite rare. To augment current dataset, messages from other languages (english only for now) have been integrated. |
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To integrate other languages dataset, MT model were used and manually selected for each dataset. |
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- UC-Berkeley-Measuring-Hate-Speech dataset : Abelll/marian-finetuned-kde4-en-to-fr |
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### Language verification |
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Since MT models are not perfect, some messages are not entirely translated or not translated at all. |
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To check for obvious errors in pipeline, a general language detection model is used to prune non french texts. |
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Language detection model : papluca/xlm-roberta-base-language-detection |
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### Annotation |
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Since "hate speech" dimension is highly subjective, and datasets comes with different annotations types, a conventional labeling stategy is required. |
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Each sample is annotated with "0" if negative sample and "1" if positive sample. |
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### Filtering rules : |
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- FTR dataset : [wip] |
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- MLMA dataset : [wip] |
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- CAA dataset : [wip] |
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- "Annotated Corpus" dataset : [wip] |
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- UC-Berkeley Measuring Hate Speech dataset : average hate_speech_score > 0 -> 1 |
