---
task_categories:
- text-classification
language:
- pt
pretty_name: HateBR - Offensive Language and Hate Speech Dataset in Brazilian Portuguese
size_categories:
- 1K<n<10K
---
# Dataset Card for HateBR - Offensive Language and Hate Speech Dataset in Brazilian Portuguese

## Dataset Description

- **Homepage:** 
- **Repository:** https://github.com/franciellevargas/HateBR
- **Paper:** https://aclanthology.org/2022.lrec-1.777/
- **Leaderboard:** 
- **Point of Contact:** https://franciellevargas.github.io/

### Dataset Summary

HateBR is the first large-scale expert annotated corpus of Brazilian Instagram comments for hate speech and offensive language detection on the web and social media. The HateBR corpus 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 nine hate speech groups (xenophobia, racism, homophobia, sexism, religious intolerance, partyism, apology for the dictatorship, antisemitism, and fatphobia). Each comment was annotated by three different annotators and achieved high inter-annotator agreement. Furthermore, baseline experiments were implemented reaching 85% of F1-score outperforming the current literature models for the Portuguese language. Accordingly, we hope that the proposed expertly annotated corpus may foster research on hate speech and offensive language detection in the Natural Language Processing area.

### Supported Tasks and Leaderboards

Hate Speech Detection, Hate 

### Languages

Portuguese

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

* instagram_comments: Instagram comments.
* offensive_language: Offensive language classification divided into offensive comments versus non-offensive comments.
* offensiveness_levels: Offensiveness-level classification divided into highly offensive, moderately offensive, and slightly offensive.
* hate_speech: Hate speech classification divided into nine different hate groups: antisemitism, apology for the dictatorship, fatphobia, homophobia, partyism, racism, religious intolerance, sexism, and xenophobia. At last, offensive & no hate speech comments also was classified.

### Data Splits

No standard splits have been provided by the authors.

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

[More Information Needed]