Rumor Containment by Spreading Correct Information in Social Networks

Rumors can propagate at great speed through social networks and produce significant damages. In order to control rumor propagation, spreading correct information to counterbalance the effect of the rumor seems more appropriate than simply blocking rumors by censorship or network disruption. In this paper, a competitive diffusion model, namely Linear Threshold model with One Direction state Transition (LT1DT), is proposed for modeling competitive information propagation of two different types in the same network. Unlike other competitive diffusion models in which individual beliefs do not change once adopted, LT1DT can model the behavior of a person that, although initially influenced by the rumor, can change his/her mind when receiving correct information. The problem of minimizing rumor spread in social networks is explored. Several simulations on two real-world datasets using four heuristic approaches are presented.