Datasets:

franciellevargas
/

HateBR

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-# Dataset Card for Dataset Name
-HateBR is the first large-scale expert annotated dataset of Brazilian Instagram comments for hate speech detection on the web and social media.
-The HateBR was collected from Brazilian Instagram comments of politicians and manually annotated by specialists.
-It is composed of 7,000 documents annotated according to three different layers: a binary classification
-(offensive versus non-offensive comments), offensiveness-level (highly, moderately, and slightly offensive messages), and
-hate speech targets. Each comment was annotated by three different expert annotators and achieved high inter-annotator agreement.
-We hope that the proposed expert annotated dataset may foster research on hate speech detection in the Natural Language Processing area.
-## Dataset Details
-### Dataset Description
-<!-- Provide a longer summary of what this dataset is. -->
-- **Curated by:** [More Information Needed]
-- **Funded by Francielle Vargas:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
 - **Language(s) (NLP):** Portuguese
-- **License:** [More Information Needed]
 ### Dataset Sources [optional]
-<!-- Provide the basic links for the dataset. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the dataset is intended to be used. -->
-### Direct Use
-<!-- This section describes suitable use cases for the dataset. -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-[More Information Needed]
-## Dataset Structure
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-[More Information Needed]
-## Dataset Creation
-### Curation Rationale
-<!-- Motivation for the creation of this dataset. -->
-[More Information Needed]
-### Source Data
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-#### Data Collection and Processing
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-[More Information Needed]
-#### Who are the source data producers?
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-[More Information Needed]
-### Annotations [optional]
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-#### Annotation process
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-[More Information Needed]
-#### Who are the annotators?
-<!-- This section describes the people or systems who created the annotations. -->
-[More Information Needed]
-#### Personal and Sensitive Information
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-[More Information Needed]
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
-**BibTeX:**
-[More Information Needed]
-**APA:**
-[More Information Needed]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Dataset Card Authors [optional]
-[More Information Needed]
 ## Dataset Card Contact
-[More Information Needed]

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+# 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 three expert annotators, resulting in a high level of inter-annotator agreement.
+We hope that this expert-annotated dataset will contribute to advancing research in hate speech detection within the field of Natural Language Processing.
+### Dataset Description
+- **Curated by:** Francielle Vargas
+- **Funded by Francielle Vargas:** <https://franciellevargas.github.io/>
 - **Language(s) (NLP):** Portuguese
 ### Dataset Sources [optional]
+- **Repository:** https://github.com/franciellevargas/HateBR
+- **Demo:** NoHateBrazil (Brasil-Sem-Ódio): http://143.107.183.175:14581/
+- **Paper:**
+@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#}, }
 ## Dataset Card Contact
+[email protected]