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+ For the shared task [CLEF TextDetox 2024](https://pan.webis.de/clef24/pan24-web/text-detoxification.html), we provide a compilation of binary toxicity classification datasets for each language.
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+ Namely, for each language, we provide 5k subparts of the datasets -- 2.5k toxic and 2.5k non-toxic samples.
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+ The list of original sources:
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+ * English: [Jigsaw](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge), [Unitary AI Toxicity Dataset](https://github.com/unitaryai/detoxify)
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+ * Russian: [Russian Language Toxic Comments](https://www.kaggle.com/datasets/blackmoon/russian-language-toxic-comments), [Toxic Russian Comments](https://www.kaggle.com/datasets/alexandersemiletov/toxic-russian-comments)
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+ * Ukrainian: ours
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+ * Spanish: [CLANDESTINO, the Spanish toxic language dataset](https://github.com/microsoft/Clandestino/tree/main)
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+ * German: [DeTox-Dataset](https://github.com/hdaSprachtechnologie/detox), [GemEval 2018, 2021](https://aclanthology.org/2021.germeval-1.1/)
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+ * Amhairc:
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+ * Arabic:
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+ * Hindi: [Hostility Detection Dataset in Hindi](https://competitions.codalab.org/competitions/26654#learn_the_details-dataset), [Overview of the HASOC track at FIRE 2019: Hate Speech and Offensive Content Identification in Indo-European Languages](https://dl.acm.org/doi/pdf/10.1145/3368567.3368584?download=true)
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+ All credits go to the authors of the original toxic words lists.