task_categories:text-classification annotations_creators:expert-generated language_creators:found multilinguality:monolingual size_categories:1K<n<10K source_datasets:original language:pt license:unknown hate-speech-detection region:us
Portuguese dataset for hate speech detection composed of 5,668 tweets with binary annotations (i.e. 'hate' vs. 'no-hate').
@inproceedings{fortuna-etal-2019-hierarchically,
title = "A Hierarchically-Labeled {P}ortuguese Hate Speech Dataset",
author = "Fortuna, Paula  and
    Rocha da Silva, Jo{\\~a}o  and
    Soler-Company, Juan  and
    Wanner, Leo  and
    Nunes, S{\'e}rgio",
booktitle = "Proceedings of the Third Workshop on Abusive Language Online",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/W19-3510",
doi = "10.18653/v1/W19-3510",
pages = "94--104",
abstract = "Over the past years, the amount of online offensive speech has been growing steadily. To successfully cope with it, machine learning are applied. However, ML-based techniques require sufficiently large annotated datasets. In the last years, different datasets were published, mainly for English. In this paper, we present a new dataset for Portuguese, which has not been in focus so far. The dataset is composed of 5,668 tweets. For its annotation, we defined two different schemes used by annotators with different levels of expertise. Firstly, non-experts annotated the tweets with binary labels ({`}hate{'} vs. {`}no-hate{'}). Secondly, expert annotators classified the tweets following a fine-grained hierarchical multiple label scheme with 81 hate speech categories in total. The inter-annotator agreement varied from category to category, which reflects the insight that some types of hate speech are more subtle than others and that their detection depends on personal perception. This hierarchical annotation scheme is the main contribution of the presented work, as it facilitates the identification of different types of hate speech and their intersections. To demonstrate the usefulness of our dataset, we carried a baseline classification experiment with pre-trained word embeddings and LSTM on the binary classified data, with a state-of-the-art outcome.",
}
---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- pt
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids: []
pretty_name: HateSpeechPortuguese
tags:
- hate-speech-detection
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': no-hate
          '1': hate
  - name: hatespeech_G1
    dtype: string
  - name: annotator_G1
    dtype: string
  - name: hatespeech_G2
    dtype: string
  - name: annotator_G2
    dtype: string
  - name: hatespeech_G3
    dtype: string
  - name: annotator_G3
    dtype: string
  splits:
  - name: train
    num_bytes: 826130
    num_examples: 5670
  download_size: 763846
  dataset_size: 826130
---

# Dataset Card for [Dataset Name]

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** https://github.com/paulafortuna/Portuguese-Hate-Speech-Dataset
- **Repository:** https://github.com/paulafortuna/Portuguese-Hate-Speech-Dataset
- **Paper:** https://www.aclweb.org/anthology/W19-3510/
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

Portuguese dataset for hate speech detection composed of 5,668 tweets with binary annotations (i.e. 'hate' vs. 'no-hate').

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

[More Information Needed]

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

[More Information Needed]

### Data Splits

[More Information Needed]

## 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

Thanks to [@hugoabonizio](https://github.com/hugoabonizio) for adding this dataset.