Analysis of misinformation containment in online social networks

With their blistering expansion in recent years, popular online social sites such as Twitter, Facebook and Bebo, have become not only one of the most effective channels for viral marketing but also the major news sources for many people nowadays. Alongside these promising features, however, comes the threat of misinformation propagation which can lead to undesirable effects. Due to the sheer number of online social network (OSN) users and the highly clustered structures commonly shared by these kinds of networks, there is a substantial challenge to efficiently contain viral spread of misinformation in large-scale social networks. In this paper, we focus on how to limit viral propagation of misinformation in OSNs. Particularly, we study a set of problems, namely the b I T-Node Protectors problems, which aim to find the smallest set of highly influential nodes from which disseminating good information helps to contain the viral spread of misinformation, initiated from a set of nodes I, within a desired fraction ð1 À bÞ of the nodes in the entire network in T time steps. For this family of problems, we analyze and present solutions including their inap-proximability results, greedy algorithms that provide better lower bounds on the number of selected nodes, and a community-based method for solving these problems. We further conduct a number of experiments on real-world traces, and the empirical results show that our proposed methods outperform existing alternative approaches in finding those important nodes that can help to contain the spread of misinformation effectively. The growing popularity of online social networks, together with their diversity, has drastically changed the landscape of communications and information sharing in cyber-space. Many people have integrated popular online social sites, such as Facebook and Twitter, into their everyday lives and rely on them as one of their major news sources. For example, the news of the hit on Bin Laden first broke out on Twitter long before the US president officially announced it on the public media [1], or the recent event Occupy of Wall Street has been spread quickly and widely to a larger population due to its Facebook page [2]. The popularity of OSNs, as a result, is obtained from the convenience as well as efficiency of information dissemination and sharing based on the trust relationships built among their users. Unfortunately, such trust relationships on social networks can possibly be exploited for distributing misinformation or rumors that could potentially cause …