A Motif-Based Framework for Characterizing the Evolution of Social Networks

Abstract

Social network computing has become popular in recent years. The study of evolving patterns of networks is facing a challenge: how to find the evolving features so as to extract significant evolving patterns. In this work, a novel framework based on network motifs is proposed to characterize the evolution of networks, capture the behavioral tendencies that contribute to the evolution of the network, and then identify evolving significantly behaviors. We show the results of extensive exploration on a real social news network, which demonstrate that the proposed scheme will contribute to the understanding of the evolving characteristic of social networks.