Datasets:
license: apache-2.0
task_categories:
- text-classification
language:
- pt
tags:
- hate
- hatespeech
- brazilianportuguese
- evaluationbenchmark
- naturallanguageprocessing
- machinelearning
pretty_name: HateBR
HateBR: The Evaluation Benchmark for Brazilian Portuguese Hate Speech Detection
HateBR is the first large-scale, expert-annotated dataset of Brazilian Instagram comments specifically designed for hate speech detection on the web and social media. The dataset was collected from Brazilian Instagram comments made by politicians and manually annotated by specialists.
It contains 7,000 documents, annotated across three distinct layers:
Binary classification (offensive vs. non-offensive comments), Offensiveness level (highly, moderately, and slightly offensive messages), Hate speech targets.
Each comment was annotated by 3 (three) expert annotators, resulting in a high level of inter-annotator agreement.
Dataset Description
- Curated by: Francielle Vargas
- Funded by: Francielle Vargas:** https://franciellevargas.github.io/
- Language(s) (NLP): Portuguese
Dataset Sources
- Repository: https://github.com/franciellevargas/HateBR
- Demo: NoHateBrazil (Brasil-Sem-Ódio): http://143.107.183.175:14581/
- 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", }
@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}, 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#}, }