Containment of rumor spread in complex social networks.

• A non-progressive diffusion model is proposed to describe the competitive propagation of two pieces of information or products. • The problem of minimizing rumor spread in social networks is studied and proved to be NP-hard. • A novel heuristic based on diffusion dynamics is proposed to solve the problem of minimizing rumor spread and compared with two adaptations of well-known ones. • A series of experiments are conducted on four different 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. The problem of minimizing rumor spread in social networks is explored and a novel heuristic based on diffusion dynamics is proposed to solve this problem under the LT1DT. Experimental analysis on four different networks shows that the novel heuristic outperforms pagerank centrality. By seeding correct information in the proximity of rumor seeds, the novel heuristic performs as well as the greedy approach in scale-free and small-world networks but runs three orders of magnitude faster than the greedy approach. [ABSTRACT FROM AUTHOR]