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Erschienen in:
2021 | OriginalPaper | Buchkapitel
Graph Mining Meets Fake News Detection
verfasst von : Kaiqiang Yu, Cheng Long
Erschienen in: Data Science for Fake News
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Nowadays, the diversified services on social media make news diffused at higher rate and larger volumes, which poses unique challenges in terms of the efficiency, scalability, and accuracy on the fake news detection. To solve these issues, graph mining, as a promising direction of data mining, has successfully attracted attentions of recent studies. In this chapter, we present a comprehensive study on recent graph-based fake news detection approaches and show how graph mining enables the whole task. We first introduce different kinds of information related to fake news, then divide the existing graph-based approaches into two scenarios, where various graphs and graph patterns are introduced to model the information on social media and characterize features of the fake news, respectively.