CFP last date
22 September 2025
Call for Paper
October Edition
IJCA solicits high quality original research papers for the upcoming October edition of the journal. The last date of research paper submission is 22 September 2025

Submit your paper
Know more
The week's pick
Responsive image
RESPONSIVE WEB DESIGN FOR ENHANCED USER EXPERIENCE (UX) AND USER INTERFACE (UI)

Victor Aienobe Muhammad Zahid Iqbal
Random Articles
Reseach Article

Arabic Misinformation Detection on Social Media: Methods, Challenges, and Future Directions

by Esraa Hamdy, Tarek Elghazaly, Sarah Saad Eldin
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 33
Year of Publication: 2025
Authors: Esraa Hamdy, Tarek Elghazaly, Sarah Saad Eldin
10.5120/ijca2025925610

Esraa Hamdy, Tarek Elghazaly, Sarah Saad Eldin . Arabic Misinformation Detection on Social Media: Methods, Challenges, and Future Directions. International Journal of Computer Applications. 187, 33 ( Aug 2025), 45-52. DOI=10.5120/ijca2025925610

@article{ 10.5120/ijca2025925610,
author = { Esraa Hamdy, Tarek Elghazaly, Sarah Saad Eldin },
title = { Arabic Misinformation Detection on Social Media: Methods, Challenges, and Future Directions },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2025 },
volume = { 187 },
number = { 33 },
month = { Aug },
year = { 2025 },
issn = { 0975-8887 },
pages = { 45-52 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number33/arabic-misinformation-detection-on-social-media-methods-challenges-and-future-directions/ },
doi = { 10.5120/ijca2025925610 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-08-20T21:35:37.053251+05:30
%A Esraa Hamdy
%A Tarek Elghazaly
%A Sarah Saad Eldin
%T Arabic Misinformation Detection on Social Media: Methods, Challenges, and Future Directions
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 33
%P 45-52
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the digital age, the widespread dissemination of misinformation and fake news poses significant threats to public opinion, social trust, and decision-making processes. This survey provides a comprehensive overview of recent advances in fake news detection, with a particular focus on techniques involving preprocessing, text representation, and classification. We further examine related tasks such as claim detection and veracity prediction, which form the backbone of automated fact-checking systems. The survey also explores some of the Arabic fake news detection datasets that have been published for various tasks. This work aims to offer valuable insights into current research trends, identify existing challenges, and highlight potential directions for future developments in the fight against misinformation.

References
  1. A. B. Nassif, A. Elnagar, O. Elgendy, and Y. Afadar, "Arabic fake news detection based on deep contextualized embedding models," Neural Computing and Applications, vol. 34, no. 18, pp. 16019-16032, 2022.
  2. I. kh. Alnabrisi and M. kh. Saad, “Detect Arabic fake news through deep learning models and Transformers,” Expert Systems with Application, vol. 251, p. 123997, 2024.
  3. R. Panchendrarajan and A. Zubiaga, "Claim detection for automated fact-checking: A survey on monolingual, multilingual and cross-lingual research," Natural Language Processing Journal, vol. 7, p. 100066, 2024.
  4. T. Alotaibi and H. Al-Dossari, “A Review of Fake News Detection Techniques for Arabic Language,” Int. J. Adv. Comput. Sci. Appl., vol. 15, no. 1, pp. 392–407, 2024.
  5. W. Shishah, “JointBert for Detecting Arabic Fake News,” IEEE Access, vol. 10, no. July, pp. 71951–71960, 2022.
  6. T. Thaher, M. Saheb, H. Turabieh, and H. Chantar, "Intelligent detection of false information in arabic tweets utilizing hybrid harris hawks based feature selection and machine learning models," Symmetry, vol. 13, no. 4, p. 556, 2021.
  7. S. N. Qasem, M. Al-Sarem, and F. Saeed, “An ensemble learning based approach for detecting and tracking COVID19 rumors,” Comput. Mater. Contin., vol. 70, no. 1, pp. 1721–1747, 2021.
  8. H. Himdi, G. Weir, F. Assiri, and H. Al-Barhamtoshy, “Arabic fake news detection based on textual analysis,” Arab. J. Sci. Eng., vol. 47, no. 8, pp. 10453–10469, 2022.
  9. A. Dahou et al., “Linguistic feature fusion for Arabic fake news detection and named entity recognition using reinforcement learning and swarm optimization,” Neurocomputing, vol. 598, no. March, p. 128078, 2024.
  10. T. Aljrees, “Improving Prediction of Arabic Fake News Using ELMO’s Features-Based Tri-Ensemble Model and LIME XAI,” IEEE Access, vol. 12, no. February, pp. 63066–63076, 2024.
  11. H. Najadat, M. Tawalbeh, and R. Awawdeh, “Fake news detection for Arabic headlines-articles news data using deep learning,” Int. J. Electr. Comput. Eng., vol. 12, no. 4, pp. 3951–3959, 2022.
  12. A. Dahou et al., "Optimizing fake news detection for Arabic context: A multitask learning approach with transformers and an enhanced Nutcracker Optimization Algorithm," Knowledge-Based Systems, vol. 280, p. 111023, 2023.
  13. M. Abd Elaziz, A. Dahou, D. A. Orabi, S. Alshathri, E. M. Soliman, and A. A. Ewees, “A Hybrid Multitask Learning Framework with a Fire Hawk Optimizer for Arabic Fake News Detection,” Mathematics, vol. 11, no. 2, pp. 1–15, 2023, doi: 10.3390/math11020258.
  14. R. M. Albalawi, A. T. Jamal, A. O. Khadidos, and A. M. Alhothali, “Multimodal Arabic Rumors Detection,” IEEE Access, vol. 11, no. December 2022, pp. 9716–9730, 2023, doi: 10.1109/ACCESS.2023.3240373.
  15. H. J. Alshahrani et al., "Hunter Prey Optimization with Hybrid Deep Learning for Fake News Detection on Arabic Corpus," Computers, Materials & Continua, vol. 75, no. 2, 2023.
  16. M. R. Hossain, M. M. Hoque, N. Siddique, and M. A. A. Dewan, "AraCovTexFinder: Leveraging the transformer-based language model for Arabic COVID-19 text identification," Engineering Applications of Artificial Intelligence, vol. 133, p. 107987, 2024.
  17. N. A. Othman, D. S. Elzanfaly, and M. M. M. Elhawary, “Arabic Fake News Detection Using Deep Learning,” IEEE Access, 2024.
  18. A. Y. Muaad, H. J. Davanagere, J. Hussain, and M. A. Al-antari, "Deep ensemble transfer learning framework for COVID-19 Arabic text identification via deep active learning and text data augmentation," Multimedia Tools and Applications, vol. 83, no. 33, pp. 79337-79375, 2024.
  19. E. Aljohani, "Enhancing Arabic Fake News Detection: Evaluating Data Balancing Techniques Across Multiple Machine Learning Models," Engineering, Technology & Applied Science Research, vol. 14, no. 4, pp. 15947-15956, 2024.
  20. L. Al-Zahrani and M. Al-Yahya, "Pre-trained language model ensemble for Arabic fake news detection," Mathematics, vol. 12, no. 18, pp. 1-17, 2024.
  21. E. A. Mohamed, W. N. Ismail, O. A. S. Ibrahim, and E. M. Younis, "A two-stage framework for arabic social media text misinformation detection combining data augmentation and arabert," Social Network Analysis and Mining, vol. 14, no. 1, p. 53, 2024.
  22. M. E. Almandouh, M. F. Alrahmawy, M. Eisa, M. Elhoseny, and A. Tolba, "Ensemble based high performance deep learning models for fake news detection," Scientific Reports, vol. 14, no. 1, p. 26591, 2024.
  23. H. M. Turki et al., "Arabic fake news detection using hybrid contextual features," International Journal of Electrical & Computer Engineering (2088-8708), vol. 15, no. 1, 2025.
  24. M. Hasanain and T. Elsayed, "bigIR at CheckThat! 2020: Multilingual BERT for ranking Arabic tweets by check-worthiness," 2020.
  25. Y. S. Kartal and M. Kutlu, "TOBB ETU at CheckThat! 2020: Prioritizing English and Arabic Claims Based on Check-Worthiness," in CLEF (Working Notes), 2020.
  26. E. Williams, P. Rodrigues, and S. Tran, "Accenture at CheckThat! 2021: interesting claim identification and ranking with contextually sensitive lexical training data augmentation," arXiv preprint arXiv:2107.05684, 2021.
  27. B. Taboubi, M. A. B. Nessir, and H. Haddad, "iCompass at CheckThat!-2022: ARBERT and AraBERT for Arabic Checkworthy Tweet Identification," in CLEF (Working Notes), 2022, pp. 702-709.
  28. S. Agresti, S. A. Hashemian, and M. J. Carman, "PoliMi-FlatEarthers at CheckThat!-2022: GPT-3 applied to claim detection," CLEF (Working Notes), vol. 2022, 2022.
  29. P. Tarannum, M. A. Hasan, F. Alam, and S. R. H. Noori, "Z-Index at CheckThat!-2023: Unimodal and Multimodal Check-worthiness Classification," in CLEF (Working Notes), 2023, pp. 482-493.
  30. A. Aziz, M. A. Hossain, and A. N. Chy, "CSECU-DSG at CheckThat!-2023: Transformer-based Fusion Approach for Multimodal and Multigenre Check-Worthiness," in CLEF (Working Notes), 2023, pp. 279-288.
  31. P. R. Aarnes, V. Setty, and P. Galuščáková, "Iai group at checkthat! 2024: Transformer models and data augmentation for checkworthy claim detection," arXiv preprint arXiv:2408.01118, 2024.
  32. M. Sawiński, K. Węcel, and E. Księżniak, "OpenFact at CheckThat! 2024: Cross-Lingual Transfer Learning for Check-Worthiness Detection," in CEUR Workshop Proceedings, 2024, vol. 3740.
  33. I. Touahri and A. Mazroui, "EvolutionTeam at CLEF2020-CheckThat! Lab: Integration of linguistic and sentimental features in a fake news detection approach," in CLEF (working notes), 2020.
  34. F. Haouari, T. Elsayed, and R. Suwaileh, "AuRED: enabling Arabic rumor verification using evidence from authorities over Twitter," in Proceedings of The Second Arabic Natural Language Processing Conference, 2024, pp. 27-41.
  35. S. Althabiti, M. A. Alsalka, and E. Atwell, "Ta'keed: The First Generative Fact-Checking System for Arabic Claims," arXiv preprint arXiv:2401.14067, 2024.
  36. A. Al Zaatari et al., "Arabic corpora for credibility analysis," in Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), 2016, pp. 4396-4401.
  37. F. A. Alqahtani and M. Sanderson, "Generating a lexicon for the Hijazi dialect in Arabic," in International Conference on Arabic Language Processing, 2019: Springer, pp. 3-17.
  38. M. S. H. Ameur and H. Aliane, "AraCOVID19-MFH: Arabic COVID-19 multi-label fake news & hate speech detection dataset," Procedia Computer Science, vol. 189, pp. 232-241, 2021.
  39. F. Haouari, M. Hasanain, R. Suwaileh, and T. Elsayed, "ArCOV19-rumors: Arabic COVID-19 twitter dataset for misinformation detection," arXiv preprint arXiv:2010.08768, 2020.
  40. T. Alhindi, A. Alabdulkarim, A. Alshehri, M. Abdul-Mageed, and P. Nakov, "Arastance: A multi-country and multi-domain dataset of arabic stance detection for fact checking," arXiv preprint arXiv:2104.13559, 2021.
  41. S. Alqurashi, B. Hamoui, A. Alashaikh, A. Alhindi, and E. Alanazi, "Eating garlic prevents COVID-19 infection: Detecting misinformation on the Arabic content of Twitter," arXiv preprint arXiv:2101.05626, 2021.
Index Terms

Computer Science
Information Sciences

Keywords

Misinformation detection – Arabic Fake News – Machine Learning – Automated Fact checking – Social Media

Powered by PhDFocusTM