Influence maximization in multiple online social networks

We study the influence maximization problem (IMP) in multiple online social networks (OSNs). In contrast to most of the previous works on influence maximization which only focused on a single network, our work is the first one to evaluate the propagation of influence across multiple networks simultaneously. In this paper, we first propose a general representation for multiple networks using universal ids for the users. We next introduce a powerful coupling scheme which reduces the multiple networks into a single network without changing influencing properties, thereby allowing us to solve the problem in the reduced network. Moreover, the coupling scheme is also an efficient tool to investigate various aspects of the influence propagation on multiple OSNs. The extensive experiments on real-world and synthesized datasets not only confirm the quality of the solution but also reveal interesting insights into the behavior of influence propagation in and across the networks.