Detection of Disinformation on Social Platforms: A Review of Computational Approaches and Challenges
Telman D. Yerimbetova A. Daiyrbayeva E. Sambetbayeva M. Abdygalym B. Turganbayev A.
2025Institute of Electrical and Electronics Engineers Inc.
International Conference on Computer Science and Engineering, UBMK
2025Issue 2025521 - 526 pp.
The rapid spread of disinformation through social platforms poses a serious threat to public trust, democratic stability, and public welfare. Researchers have proposed various computational methods for fake news detection, ranging from traditional machine learning methods to advanced deep learning models and hybrid models. This review systematically analyzes 83 peer-reviewed studies, classifying them by methodological approach, feature types, data sources, and detection strategies. The paper highlights notable advances in transformer-based models, multimodal systems integrating text and images, and graph-based spread detection. It also addresses key challenges in the field, such as the lack of multilingual datasets, explainability, and resilience to adversarial content. By identifying trends, gaps, and future directions, this review provides a comprehensive framework to advance the development of robust and transparent fake news detection systems.
deep learning , disinformation , fake news detection , machine learning , social media , transformer models
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Satbayev University, Institute of Information and Computational Technologies of the Committee of Science, Ministry of Science and Higher Education of the Republic of Kazakhstan, Almaty, Kazakhstan
Institute of Information and Computational Technologies of the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan, Almaty, Kazakhstan
L.N. Gumilyov Eurasian National University, Astana, Kazakhstan
Satbayev University
Institute of Information and Computational Technologies of the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan
L.N. Gumilyov Eurasian National University
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