A Multilingual and Multimodal Framework for Real-Time Fake News Detection on Social Media

Finally, this proposed framework represents a robust strategy for fake news detection in real time on social media sites by exploiting language-based cues as well as inconsistencies in visual content. The high training and validation accuracies indicate effective training of the architecture and good ability to generalize from the training set to unseen cases. On the other hand, the developed framework is also practical and scalable which makes it applicable in real life. Therefore, this project demonstrates the value of using multimodal and multilingual learning for developing reliable fake news detection mechanisms.

1.                            C. Castillo, M. Mendoza, and B. Poblete, “Information credibility on Twitter,” in Proc. WWW, 2011, pp. 675–684. 2.                            J. Ma, W. Gao, and K.-F. Wong, “Rumor detection on Twitter with tree-structured recursive neural networks,” in Proc. ACL, 2018, pp. 198–203. 3.                            J. Ma, W. Gao, P. Mitra, S. Kwon, and B. J. Jansen, “Detecting rumors from microblogs with recurrent neural networks,” in Proc. IJCAI, 2016, pp. 3818–3824. 4.                            Z. Jin, J. Cao, Y. Zhang, J. Zhou, and Q. Tian, “News verification by exploiting conflicting social viewpoints in microblogs,” in Proc. AAAI, 2016, pp. 2972–2978. 5.                            H. Rashkin, E. Choi, J. Y. Jang, S. Volkova, and Y. Choi, “Truth of varying shades: Analyzing language in fake news and political fact-checking,” in Proc. EMNLP, 2017, pp. 2931–2937. 6.                            K. Shu, A. Sliva, S. Wang, J. Tang, and H. Liu, “Fake news detection on social media: A data mining perspective,” SIGKDD Explorations, vol. 19, no. 1, pp. 22–36, 2017. 7.                            K. Shu, H. Liu, S. Wang, and J. Tang, “FakeNewsNet: A data repository with news content, social context and dynamic information for studying fake news on social media,” arXiv preprint arXiv:1809.01286, 2018. 8.                            S. Vosoughi, D. Roy, and S. Aral, “The spread of true and false news online,” Science, vol. 359, no. 6380, pp. 1146–1151, 2018. 9.                            N. Hassan, A. S. A. Salloum, M. A. Islam, and K. Shaalan, “A survey on fake news detection,” IEEE Access, vol. 10, pp. 1240–1258, 2022. 10.                      S. Singhal, S. Ghosh, and A. Bharadwaj, “SpotFake: A multi-modal framework for fake news detection,” in Proc. BigMM, 2019, pp. 39–46.