Limiting the spread of misinformation in social networks

In this work, we study the notion of competing campaigns in a social network. By modeling the spread of influence in the presence of competing campaigns, we provide necessary tools for applications such as emergency response where the goal is to limit the spread of misinformation. We study the problem of influence limitation where a “bad” campaign starts propagating from a certain node in the network and use the notion of limiting campaigns to counteract the effect of misinformation. The problem can be summarized as identifying a subset of individuals that need to be convinced to adopt the competing (or“good”) campaign so as to minimize the number of people that adopt the “bad” campaign at the end of both propagation processes. We show that this optimization problem is NP-hard and provide approximation guarantees for a greedy solution for various definitions of this problem by proving that they are submodular. Although the greedy algorithm is a polynomial time algorith...

• Type: Journal
• Year: 2011
• Where: WWW
• Authors: Ceren Budak, Divyakant Agrawal, Amr El Abbadi
• Keywords: Algorithms, Internet Technology, Misinformation, Social Networks, WWW 2011