Resources Building for Arabic Harmful Online Content: Survey

Fatiha Charef; Abdelhafid Zitouni; Mahieddine Djoudi; Hichem Rahab

doi:10.2991/978-94-6463-496-9_29

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Resources Building for Arabic Harmful Online Content: Survey

Authors

Fatiha Charef¹^{, *}, Abdelhafid Zitouni², Mahieddine Djoudi³, Hichem Rahab⁴

¹University Center of Aflou, Aflou, Algeria

²LIRE Laboratory, University of Constantine 2, El Khroub, Algeria

³TechNE Laboratory, University of Poitiers, Poitiers, France

⁴ICOSI Laboratory, University of Khenchela, Khenchela, Algeria

^*Corresponding author. Email: f.charef@cu-aflou.edu.dz

Corresponding Author

Fatiha Charef

Available Online 31 August 2024.

DOI: 10.2991/978-94-6463-496-9_29 How to use a DOI?
Keywords: Harmful online content; Fake news; Offensive language; NLP; Arabic datasets
Abstract: Users of social networks and Internet sites face numerous challenges. Problems such as fake news, satire, rumors, misinformation, misleading information, cyberbullying, spam content, offensive language, hate, and offensive speech fall under the category of harmful online content (HOC). This danger has taken advantage of social media’s popularity and the abundance of news that spreads quickly, causing problems for individuals and society. Moreover, to combat this danger, researchers in the AI domain have persistently advanced and proposed novel approaches across various domains. Given the progress made in this work, choosing data to evaluate their approaches was always a challenge. Our contribution aims to identify the process and criteria for creating a high-quality dataset for HOC detection, primarily in the Arabic news domain. Therefore, we have collected a list of existing and available Arabic datasets, identified their characteristics, and determined the purpose of their creation. Researchers can use our study’s results as a reference to choose an appropriate dataset for their future research.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the International Conference on Emerging Intelligent Systems for Sustainable Development (ICEIS 2024)
Series: Advances in Intelligent Systems Research
Publication Date: 31 August 2024
ISBN: 978-94-6463-496-9
ISSN: 1951-6851
DOI: 10.2991/978-94-6463-496-9_29 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Fatiha Charef
AU  - Abdelhafid Zitouni
AU  - Mahieddine Djoudi
AU  - Hichem Rahab
PY  - 2024
DA  - 2024/08/31
TI  - Resources Building for Arabic Harmful Online Content: Survey
BT  - Proceedings of the International Conference on Emerging Intelligent Systems for Sustainable Development (ICEIS 2024)
PB  - Atlantis Press
SP  - 387
EP  - 403
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-496-9_29
DO  - 10.2991/978-94-6463-496-9_29
ID  - Charef2024
ER  -

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