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.

在线社交网络提供了一个机会，可以快速，广泛地传播消息和新闻。人们可能会欣赏合法新闻和消息的迅速传播，但错误信息也会迅速传播，并可能引起人们的关注，质疑这种网络的可靠性和信任度。结果，检测错误信息并控制其传播已成为社交网络分析中的热门话题。当检测到错误信息时，可能需要采取一些措施来减少其传播和对网络的影响。此类措施旨在最大程度地减少受错误信息影响的用户数量。本文概述了解决此问题的方法，该问题可最大程度地减少错误信息在社交网络中的传播，并提出了不同方法的分类法。