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Rumor Detection with Self-supervised Learning on Texts and Social Graph. (arXiv:2204.08838v1 [cs.SI])
April 20, 2022, 1:12 a.m. | Yuan Gao, Xiang Wang, Xiangnan He, Huamin Feng, Yongdong Zhang
cs.LG updates on arXiv.org arxiv.org
Rumor detection has become an emerging and active research field in recent
years. At the core is to model the rumor characteristics inherent in rich
information, such as propagation patterns in social network and semantic
patterns in post content, and differentiate them from the truth. However,
existing works on rumor detection fall short in modeling heterogeneous
information, either using one single information source only (e.g. social
network, or post content) or ignoring the relations among multiple sources
(e.g. fusing social …
arxiv detection graph learning self-supervised learning social supervised learning
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