Analysis of the spreading influence variations for online social users under attacks

Identifying influential spreaders in online social networks (OSNs) has long been an important but difficult problem to be addressed. Distinguished from previous works that mainly focused on the stationary features of users' influence, we systematically study the variations of users' spreading capability given the fact that influential spreaders are more likely to be the targets of various cyber attacks in real OSNs. In order to rank users' spreading capability, we adopt the k-shell structure which assigns a coreness index, k s , to each user. We find that users' spreading capability can considerably change when attacks occur in specific structures of OSNs. Generally, if the OSN structure is assortative (i.e., large-degree nodes preferably connect to nodes with large degree), users' spreading capability is resilient to attacks. However, if the OSN structure is disassortative (i.e., large-degree nodes preferably connect to nodes with small degree), users' spreading capability decreases significantly under attacks. We further carried out a series of empirical studies in real OSN datasets to disclose the causation of the variations caused by attacks. The research presented in this paper benefit decision makers to protect the propagation in the case of product promotion or prevent the diffusion like rumor.