An efficient method for restraining negative information cascades in online social networks

Information cascades is recognized as a major factor in disastrous social network phenomenons. The clustering of network community can block the cascade of negative information and users' behaviors in online social networks (OSNs). Confronting limited network resources, this paper takes the interaction relationship between network structure optimizing and neighbors' behaviors cascading as the breakthrough point, and study the restrain method of negative information cascades under emergency. This paper proposes a method for restraining the cascade of negative information, which is in order to improve the clustering of network communities by means of links that are logically removed (termed CLLR). By limited links with high betweenness being logically removed, CLLR method enhances the community density in a network, thereby effectively block information cascades. Experimental results show that CLLR method significantly improve the clustering of a network, efficiently block the speed and scope of information cascades in OSNs.