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Rumor Detection on Social Media with Graph Adversarial Contrastive Learning
2022
Proceedings of the ACM Web Conference 2022
Rumors spread through the Internet, especially on Twitter, have harmed social stability and residents' daily lives. Recently, in addition to utilizing the text features of posts for rumor detection, the structural information of rumor propagation trees has also been valued. Most rumors with salient features can be quickly locked by graph models dominated by cross entropy loss. However, these conventional models may lead to poor generalization, and lack robustness in the face of noise and
doi:10.1145/3485447.3511999
fatcat:xmag5jlpznejnjoumtiblgo2t4