Datasets:
Tasks:
Text Classification
Formats:
csv
Languages:
Portuguese
Size:
1K - 10K
Tags:
hate
hatespeech
brazilianportuguese
evaluationbenchmark
naturallanguageprocessing
machinelearning
License:
Update README.md
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README.md
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- naturallanguageprocessing
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- machinelearning
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pretty_name: HateBR
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size_categories:
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- 1M<n<10M
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---
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# HateBR: The Evaluation Benchmark for Brazilian Portuguese Hate Speech Detection
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Binary classification (offensive vs. non-offensive comments),
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Offensiveness level (highly, moderately, and slightly offensive messages),
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Hate speech targets.
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Each comment was annotated by three expert annotators, resulting in a high level of inter-annotator agreement.
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We hope that this expert-annotated dataset will contribute to advancing research in hate speech detection within the field of Natural Language Processing.
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### Dataset Description
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- **Repository:** https://github.com/franciellevargas/HateBR
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- **Demo:** NoHateBrazil (Brasil-Sem-Ódio): http://143.107.183.175:14581/
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- **
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@inproceedings{vargas-etal-2022-hatebr, title = "{H}ate{BR}: A Large Expert Annotated Corpus of {B}razilian {I}nstagram Comments for Offensive Language and Hate Speech Detection", author = "Vargas, Francielle and Carvalho, Isabelle and Rodrigues de G{\'o}es, Fabiana and Pardo, Thiago and Benevenuto, Fabr{\'\i}cio", booktitle = "Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022)", year = "2022", address = "Marseille, France", publisher = "European Language Resources Association", url = "https://aclanthology.org/2022.lrec-1.777", pages = "7174--7183", }
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@article{Vargas_Carvalho_Pardo_Benevenuto_2024, author={Vargas, Francielle and Carvalho, Isabelle and Pardo, Thiago A. S. and Benevenuto, Fabrício}, title={Context-aware and expert data resources for Brazilian Portuguese hate speech detection}, DOI={10.1017/nlp.2024.18}, journal={Natural Language Processing},
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year={2024}, pages={1–22}, url={https://www.cambridge.org/core/journals/natural-language-processing/article/contextaware-and-expert-data-resources-for-brazilian-portuguese-hate-speech-detection/7D9019ED5471CD16E320EBED06A6E923#}, }
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- naturallanguageprocessing
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- machinelearning
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pretty_name: HateBR
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---
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# HateBR: The Evaluation Benchmark for Brazilian Portuguese Hate Speech Detection
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Binary classification (offensive vs. non-offensive comments),
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Offensiveness level (highly, moderately, and slightly offensive messages),
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Hate speech targets.
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Each comment was annotated by 3 (three) expert annotators, resulting in a high level of inter-annotator agreement.
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### Dataset Description
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- **Repository:** https://github.com/franciellevargas/HateBR
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- **Demo:** NoHateBrazil (Brasil-Sem-Ódio): http://143.107.183.175:14581/
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- **Papers:** @inproceedings{vargas-etal-2022-hatebr, title = "{H}ate{BR}: A Large Expert Annotated Corpus of {B}razilian {I}nstagram Comments for Offensive Language and Hate Speech Detection", author = "Vargas, Francielle and Carvalho, Isabelle and Rodrigues de G{\'o}es, Fabiana and Pardo, Thiago and Benevenuto, Fabr{\'\i}cio", booktitle = "Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022)", year = "2022", address = "Marseille, France", publisher = "European Language Resources Association", url = "https://aclanthology.org/2022.lrec-1.777", pages = "7174--7183", }
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@article{Vargas_Carvalho_Pardo_Benevenuto_2024, author={Vargas, Francielle and Carvalho, Isabelle and Pardo, Thiago A. S. and Benevenuto, Fabrício}, title={Context-aware and expert data resources for Brazilian Portuguese hate speech detection}, DOI={10.1017/nlp.2024.18}, journal={Natural Language Processing},
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year={2024}, pages={1–22}, url={https://www.cambridge.org/core/journals/natural-language-processing/article/contextaware-and-expert-data-resources-for-brazilian-portuguese-hate-speech-detection/7D9019ED5471CD16E320EBED06A6E923#}, }
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