---
task_categories:
- text-classification
language:
- ar
tags:
- hate speech
size_categories:
- 100K<n<1M
extra_gated_prompt: "You agree to not use the dataset to conduct any activity that causes harm to human subjects."
extra_gated_fields:
  Please provide more information on how you plan to use this data:
    type: text
---

# Arabic Hate Speech Superset

This dataset is a superset (N=454,427) resulting from the preprocessing and merge of all available Arabic hate speech datasets in April 2024. These datasets were identified through a systematic survey of hate speech datasets conducted in early 2024. We only kept datasets that:
- are documented
- are publicly available
- focus on hate speech, defined broadly as "any kind of communication in speech, writing or behavior, that attacks or uses pejorative or discriminatory language with reference to a person or a group on the basis of who they are, in other words, based on their religion, ethnicity, nationality, race, color, descent, gender or other identity factor" (UN, 2019)

The survey procedure is further detailed in [our survey paper](https://arxiv.org/abs/2404.17874).

## Data access and intended use
Please send an access request detailing how you plan to use the data. The main purpose of this dataset is to train and evaluate hate speech detection models, as well as study hateful discourse online. This dataset is NOT intended to train generative LLMs to produce hateful content. 

## Columns

The dataset contains six columns:
- `text`: the annotated post
- `labels`: annotation of whether the post is hateful (`== 1`) or not (`==0`). As datasets have different annotation schemes, we systematically binarized the labels.
- `source`: origin of the data (e.g., Twitter)
- `dataset`: dataset the data is from (see "Datasets" part below)
- `nb_annotators`: number of annotators by post

## Datasets

The datasets that compose this superset are:
- Let-Mi: An Arabic Levantine Twitter Dataset for Misogynistic Language (`Let-Mi` in the `dataset` column)
  - [paper link](https://aclanthology.org/2021.wanlp-1.16/)
  - [raw data link](https://drive.google.com/file/d/1mM2vnjsy7QfUmdVUpKqHRJjZyQobhTrW/view)
- Are They Our Brothers? Analysis and Detection of Religious Hate Speech in the Arabic Twittersphere (`brothers` in the `dataset` column)
  - [paper link](https://ieeexplore.ieee.org/document/8508247)
  - [raw data link](https://github.com/nuhaalbadi/Arabic_hatespeech)
- Multilingual and Multi-Aspect Hate Speech Analysis (`MLMA`)
  - [paper link](https://aclanthology.org/D19-1474/)
  - [raw data link](https://github.com/HKUST-KnowComp/MLMA_hate_speech)
- L-HSAB: A Levantine Twitter Dataset for Hate Speech and Abusive Language (`L-HSAB`)
  - [paper link](https://aclanthology.org/W19-3512/)
  - [raw data link](https://github.com/Hala-Mulki/L-HSAB-First-Arabic-Levantine-HateSpeech-Dataset)
- Hate Speech Detection in Saudi Twittersphere: A Deep Learning Approach (`saudi`)
  - [paper link](https://aclanthology.org/2020.wanlp-1.2.pdf)
  - [raw data link](https://github.com/raghadsh/Arabic-Hate-speech)
- Hate and offensive speech detection on Arabic social media (`alsafari`)
  - [paper link](https://www.sciencedirect.com/science/article/pii/S2468696420300379)
  - [raw data link](https://github.com/sbalsefri/ArabicHateSpeechDataset)
- Overview of OSACT5 Shared Task on Arabic Offensive Language and Hate Speech Detection (`OSACT`)
  - [paper link](https://aclanthology.org/2022.osact-1.20.pdf)
  - [raw data link](https://alt.qcri.org/resources1/OSACT2022/OSACT2022-sharedTask-train.txt)
- T-HSAB: A Tunisian Hate Speech and Abusive Dataset (`T-HSAB`)
  - [paper link](https://www.researchgate.net/publication/336271875_T-HSAB_A_Tunisian_Hate_Speech_and_Abusive_Dataset)
  - [raw data link](https://github.com/Hala-Mulki/T-HSAB-A-Tunisian-Hate-Speech-and-Abusive-Dataset/tree/master)
- Arabic Hate Speech Dataset 2023 (`jhsc`)
  - [paper link](https://www.preprints.org/manuscript/202309.0497/v1)
  - [raw data link](https://data.mendeley.com/datasets/mcnzzpgrdj/1)
- AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News & Hate Speech Detection Dataset (`aracovid`)
  - [paper link](https://www.sciencedirect.com/science/article/pii/S1877050921012059)
  - [raw data link](https://github.com/MohamedHadjAmeur/AraCOVID19-MFH)
 
## Additional datasets on demand
In our survey, we identified one additional dataset that is not public but can be requested to the authors, namely:
- Working Notes of the Workshop Arabic Misogyny Identification (ArMI-2021)
  - [paper link](https://www.researchgate.net/publication/358135923_Working_Notes_of_the_Workshop_Arabic_Misogyny_Identification_ArMI-2021)
  - [request link here](https://github.com/bilalghanem/armi?tab=readme-ov-file)



## Preprocessing

We drop duplicates. In case of non-binary labels, the labels are binarized (hate speech or not). We replace all usernames and links by fixed tokens to maximize user privacy. Further details on preprocessing can be found in the preprocessing code [here](https://github.com/manueltonneau/hs_geographic_survey).

## Citation
Please cite our [survey paper](https://arxiv.org/abs/2404.17874) if you use this dataset.

```bibtex
@article{tonneau2024languages,
  title={From Languages to Geographies: Towards Evaluating Cultural Bias in Hate Speech Datasets},
  author={Tonneau, Manuel and Liu, Diyi and Fraiberger, Samuel and Schroeder, Ralph and Hale, Scott A and R{\"o}ttger, Paul},
  journal={arXiv preprint arXiv:2404.17874},
  year={2024}
}
```