Community Structure Based Shortest Path Finding for Social Networks

Yale Chai, Chunyao Song, Peng Nie, Xiaojie Yuan, Yao Ge

Abstract: With the rapid expansion of communication data, research about analyzing social networks has become a hotspot. Finding the shortest path (SP) in social networks can help us to investigate the potential social relationships. However, it is an arduous task, especially on large-scale problems. There have been many previous studies on the SP problem, but very few of them considered the peculiarity of social networks. This paper proposed a community structure based method to accelerate answering the SP problem of social networks during online queries. We devise a two-stage strategy to strike a balance between offline pre-computation and online consultations. Our goal is to perform fast and accurate online approximations. Experiments show that our method can instantly return the SP result while satisfying accuracy constraint.