Minimizing the Spread of Misinformation in Online Social Networks: A Survey

Abstract

Online social networks provide an opportunity to spread messages and news fast and widely. One may appreciate the quick spread of legitimate news and messages but misinformation can also be spread quickly and may raise concerns, questioning reliability and trust in such networks. As a result, detecting misinformation and containing its spread has become a hot topic in social network analysis. When misinformation is detected, some actions may be necessary to reduce its propagation and impact on the network. Such actions aim to minimize the number of users influenced by misinformation. This paper reviews approaches for solving this problem of minimizing spread of misinformation in social networks and proposes a taxonomy of different methods