MAOffens / README.md
Randa's picture
Update README.md
59031f2 verified
metadata
license: cc-by-nc-2.0
pretty_name: Offensive Language Dataset for Moroccan Arabic dialect
task_categories:
  - text-classification
language:
  - ar
size_categories:
  - 10K<n<100K

Dataset Card for Dataset Name

This dataset card aims to be a base template for new datasets. It has been generated using this raw template.

Dataset Details

Dataset Description

  • Curated by: [More Information Needed]
  • Funded by [optional]: [More Information Needed]
  • Shared by [optional]: [More Information Needed]
  • Language(s) (NLP): [More Information Needed]
  • License: [More Information Needed]

Dataset Sources [optional]

  • Repository: [More Information Needed]
  • Paper [optional]: [More Information Needed]
  • Demo [optional]: [More Information Needed]

Uses

Direct Use

[More Information Needed]

Out-of-Scope Use

[More Information Needed]

Dataset Structure

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Data Collection and Processing

[More Information Needed]

Who are the source data producers?

[More Information Needed]

Annotations [optional]

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Bias, Risks, and Limitations

[More Information Needed]

Recommendations

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

Citation [optional]

BibTeX:

@InProceedings{10.1007/978-3-031-80438-0_2,

author="Zarnoufi, Randa and Hajhouj, Mohammed and Bachri, Walid and Jaafar, Hamid and Abik, Mounia",

editor="Hdioud, Boutaina and Aouragh, Si Lhoussain",

title="MAOffens: Moroccan Arabic Offensive Language Dataset",

booktitle="Arabic Language Processing: From Theory to Practice", year="2025", publisher="Springer Nature Switzerland", address="Cham", pages="17--29",

abstract="Moroccan Arabic (MA) dialect is a low resource language. To perform any NLP task, we have to develop the necessary resources from scratch. This paper introduces our work on MAOffens, the first MA dataset for offensive language detection. The dataset will serve to build predictive models to detect offensive content widely present on social media and hence help ensure online safety. We built the dataset with a mixture of comments in Arabic and Latin scripts to cover offensiveness in both cases. The resulting dataset consists of 23k comments totally balanced. The dataset is open to the public (https://huggingface.co/datasets/randa/maoffens). We evaluated the annotation and classification power of the dataset through various classifier architectures. Our best performing classifier was based on a MA transformer model.",

isbn="978-3-031-80438-0" }

APA:

[More Information Needed]

Glossary [optional]

[More Information Needed]

More Information [optional]

[More Information Needed]

Dataset Card Authors [optional]

[More Information Needed]

Dataset Card Contact

[More Information Needed]