Fake news detection: state-of-the-art review and advances with attention to Arabic language aspects
The proliferation of fake news has become a significant threat, influencing individuals, institutions, and societies at large. This issue has been exacerbated by the pervasive integration of social media into daily life, directly shaping opinions, trends, and even the economies of nations. Social me...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2025-03-01
|
| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-2693.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850052565818933248 |
|---|---|
| author | Eman Salamah Albtoush Keng Hoon Gan Saif A. Ahmad Alrababa |
| author_facet | Eman Salamah Albtoush Keng Hoon Gan Saif A. Ahmad Alrababa |
| author_sort | Eman Salamah Albtoush |
| collection | DOAJ |
| description | The proliferation of fake news has become a significant threat, influencing individuals, institutions, and societies at large. This issue has been exacerbated by the pervasive integration of social media into daily life, directly shaping opinions, trends, and even the economies of nations. Social media platforms have struggled to mitigate the effects of fake news, relying primarily on traditional methods based on human expertise and knowledge. Consequently, machine learning (ML) and deep learning (DL) techniques now play a critical role in distinguishing fake news, necessitating their extensive deployment to counter the rapid spread of misinformation across all languages, particularly Arabic. Detecting fake news in Arabic presents unique challenges, including complex grammar, diverse dialects, and the scarcity of annotated datasets, along with a lack of research in the field of fake news detection compared to English. This study provides a comprehensive review of fake news, examining its types, domains, characteristics, life cycle, and detection approaches. It further explores recent advancements in research leveraging ML, DL, and transformer-based techniques for fake news detection, with a special attention to Arabic. The research delves into Arabic-specific pre-processing techniques, methodologies tailored for fake news detection in the language, and the datasets employed in these studies. Additionally, it outlines future research directions aimed at developing more effective and robust strategies to address the challenge of fake news detection in Arabic content. |
| format | Article |
| id | doaj-art-a532b1e2ddce4f77a078af4a03aea01d |
| institution | DOAJ |
| issn | 2376-5992 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj-art-a532b1e2ddce4f77a078af4a03aea01d2025-08-20T02:52:46ZengPeerJ Inc.PeerJ Computer Science2376-59922025-03-0111e269310.7717/peerj-cs.2693Fake news detection: state-of-the-art review and advances with attention to Arabic language aspectsEman Salamah Albtoush0Keng Hoon Gan1Saif A. Ahmad Alrababa2School of Computer Sciences, Universiti Sains Malaysia, Gelugor, MalaysiaSchool of Computer Sciences, Universiti Sains Malaysia, Gelugor, MalaysiaFaculty of Information Technology, Al al-Bayt University, Mafraq, JordanThe proliferation of fake news has become a significant threat, influencing individuals, institutions, and societies at large. This issue has been exacerbated by the pervasive integration of social media into daily life, directly shaping opinions, trends, and even the economies of nations. Social media platforms have struggled to mitigate the effects of fake news, relying primarily on traditional methods based on human expertise and knowledge. Consequently, machine learning (ML) and deep learning (DL) techniques now play a critical role in distinguishing fake news, necessitating their extensive deployment to counter the rapid spread of misinformation across all languages, particularly Arabic. Detecting fake news in Arabic presents unique challenges, including complex grammar, diverse dialects, and the scarcity of annotated datasets, along with a lack of research in the field of fake news detection compared to English. This study provides a comprehensive review of fake news, examining its types, domains, characteristics, life cycle, and detection approaches. It further explores recent advancements in research leveraging ML, DL, and transformer-based techniques for fake news detection, with a special attention to Arabic. The research delves into Arabic-specific pre-processing techniques, methodologies tailored for fake news detection in the language, and the datasets employed in these studies. Additionally, it outlines future research directions aimed at developing more effective and robust strategies to address the challenge of fake news detection in Arabic content.https://peerj.com/articles/cs-2693.pdfFake newsArabic languageDetection approachesDatasetsMachine learning |
| spellingShingle | Eman Salamah Albtoush Keng Hoon Gan Saif A. Ahmad Alrababa Fake news detection: state-of-the-art review and advances with attention to Arabic language aspects PeerJ Computer Science Fake news Arabic language Detection approaches Datasets Machine learning |
| title | Fake news detection: state-of-the-art review and advances with attention to Arabic language aspects |
| title_full | Fake news detection: state-of-the-art review and advances with attention to Arabic language aspects |
| title_fullStr | Fake news detection: state-of-the-art review and advances with attention to Arabic language aspects |
| title_full_unstemmed | Fake news detection: state-of-the-art review and advances with attention to Arabic language aspects |
| title_short | Fake news detection: state-of-the-art review and advances with attention to Arabic language aspects |
| title_sort | fake news detection state of the art review and advances with attention to arabic language aspects |
| topic | Fake news Arabic language Detection approaches Datasets Machine learning |
| url | https://peerj.com/articles/cs-2693.pdf |
| work_keys_str_mv | AT emansalamahalbtoush fakenewsdetectionstateoftheartreviewandadvanceswithattentiontoarabiclanguageaspects AT kenghoongan fakenewsdetectionstateoftheartreviewandadvanceswithattentiontoarabiclanguageaspects AT saifaahmadalrababa fakenewsdetectionstateoftheartreviewandadvanceswithattentiontoarabiclanguageaspects |