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With the rapid development and popularization of Internet technology, the propagation and diffusion of information become much easier and faster. While making life more convenient, the Internet also promotes the wide spread of fake news, which will have a great negative impact on countries, societies, and individuals. Therefore, a lot of research efforts have been made to combat fake news. Fake news detection is typically a classification problem aiming at verifying the veracity of news contents, which may include texts, images and videos. This article provides a comprehensive survey of fake news detection. We first summarize three intrinsic characteristics of fake news by analyzing its entire diffusion process, namely intentional creation, heteromorphic transmission, and controversial reception. The first refers to why users publish fake news, the second denotes how fake news propagates and distributes, and the last means what viewpoints different users may hold for fake news. We then discuss existing fake news detection approaches according to these characteristics. Thus, this review will enable readers to better understand this field from a new perspective. We finally discuss the trends of technological advances in this field and also outline some potential directions for future research.
Hu et al. (Thu,) studied this question.