Influence Propagation over Large Scale Social Networks

Abstract

We study the influence diffusion problem in online social networks. Formally, given a network represented by a directed graph G = (V,E), we consider a process of influence diffusion in G that proceeds as follows: Initially only the vertices of a given S ⊆ V are influenced; subsequently, at each round, the set of influenced vertices is augmented by all the vertices in the network that have a sufficiently large number of already influenced incoming neighbors. The question is to find a small subset of vertices that can influence the whole network (target set). This is a widely studied problem that abstracts many phenomena in the social, economic, biological, and physical sciences. It is known to be hard to approximate within a factor of 2log1--ϵn, for any ϵ > 0, and n = |V |.