GRACE: Graph-Based Attention for Coherent Explanation in Fake News Detection on Social Media
Mamyrbayev O. Turysbek Z. Afzal M. Abdurakhimovich M.U. Galiya Y. Abdullah M. Amin R.U.
2025Science and Information Organization
International Journal of Advanced Computer Science and Applications
2025#16Issue 11159 - 1171 pp.
Detecting fake news on social media is a critical challenge due to its rapid dissemination and potential societal impact. This paper addresses the problem in a realistic scenario where the original tweet and the sequence of users who retweeted it, excluding any comment section, are available. We propose a Graph-based Attention for Coherent Explanation (GRACE) to perform binary classification by determining if the original tweet is false and provide interpretable explanations by highlighting suspicious users and key evidential words. GRACE integrates user behaviour, tweet content, and retweet propagation dynamics through Graph Convolutional Networks (GCNs) and a dual co-attention mechanism. Extensive experiments conducted on Twitter15 and Twitter16 datasets demonstrate that GRACE out- performs baseline methods, achieving an accuracy improvement of 2.12% on Twitter15 and 1.83% on Twitter16 compared to GCAN. Additionally, GRACE provides meaningful and coherent explanations, making it an effective and interpretable solution for fake news detection on social platforms.
dual attention , Graph neural network , NLP , seman- tics , social network
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Institute of Information and Computational Technologies, Almaty, Kazakhstan
Kazakh National Research Technical University, Kazakhstan
Riphah International University, Faisalabad, Pakistan
International Kazakh-Turkish University named by Khoja Akhmet Yassawi, Kazakhstan
Department of Technical and Natural Sciences, International Educational Corporation, United States
School of Computing and Artificial Intelligence, Zhengzhou University, Henan, Zhengzhou, 450001, China
School of Computing and Information Technology, University of Okara and Edinburgh, Napier University, United Kingdom
Institute of Information and Computational Technologies
Kazakh National Research Technical University
Riphah International University
International Kazakh-Turkish University named by Khoja Akhmet Yassawi
Department of Technical and Natural Sciences
School of Computing and Artificial Intelligence
School of Computing and Information Technology
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