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Dataset Card for "shaj"
Dataset Summary
This is an abusive/offensive language detection dataset for Albanian. The data is formatted following the OffensEval convention, with three tasks:
- Subtask A: Offensive (OFF) or not (NOT)
- Subtask B: Untargeted (UNT) or targeted insult (TIN)
- Subtask C: Type of target: individual (IND), group (GRP), or other (OTH)
Notes on the above:
- The subtask A field should always be filled.
- The subtask B field should only be filled if there's "offensive" (OFF) in A.
- The subtask C field should only be filled if there's "targeted" (TIN) in B.
The dataset name is a backronym, also standing for "Spoken Hate in the Albanian Jargon"
See the paper https://arxiv.org/abs/2107.13592 for full details.
Supported Tasks and Leaderboards
- Task A leaderboard at paperswithcode.com/sota/hate-speech-detection-on-shaj
Languages
Albanian (bcp47:sq-AL)
Dataset Structure
Data Instances
shaj
- Size of downloaded dataset files: 769.21 KiB
- Size of the generated dataset: 1.06 MiB
- Total amount of disk used: 1.85 MiB
An example of 'train' looks as follows.
{
'id': '0',
'text': 'PLACEHOLDER TEXT',
'subtask_a': 1,
'subtask_b': 0,
'subtask_c': 0
}
Data Fields
id: astringfeature.text: astring.subtask_a: whether or not the instance is offensive;0: OFF, 1: NOTsubtask_b: whether an offensive instance is a targeted insult;0: TIN, 1: UNT, 2: not applicablesubtask_c: what a targeted insult is aimed at;0: IND, 1: GRP, 2: OTH, 3: not applicable
Data Splits
| name | train |
|---|---|
| shaj | 11874 sentences |
Dataset Creation
Curation Rationale
Collecting data for enabling offensive speech detection in Albanian
Source Data
Initial Data Collection and Normalization
The text is scraped from comments on popular Albanian YouTube and Instagram accounts. An extended discussion is given in the paper in section 3.2.
Who are the source language producers?
People who comment on a selection of high-activity Albanian instagram and youtube profiles.
Annotations
Annotation process
The annotation scheme was taken from OffensEval 2019 and applied by two native speaker authors of the paper as well as their friends and family.
Who are the annotators?
Albanian native speakers, male and female, aged 20-60.
Personal and Sensitive Information
The data was public at the time of collection. No PII removal has been performed.
Considerations for Using the Data
Social Impact of Dataset
The data definitely contains abusive language.
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
The dataset is curated by the paper's authors.
Licensing Information
The authors distribute this data under Creative Commons attribution license, CC-BY 4.0.
Citation Information
@article{nurce2021detecting,
title={Detecting Abusive Albanian},
author={Nurce, Erida and Keci, Jorgel and Derczynski, Leon},
journal={arXiv preprint arXiv:2107.13592},
year={2021}
}
Contributions
Author-added dataset @leondz
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