Exploring community structure in networks by consensus dynamics

Abstract

This paper investigates the relationship between community structure and consensus dynamics in complex networks. We analyze the dynamical process towards consensus and show that those sets of densely interconnected nodes corresponding to well-defined communities appear in different time scales. In order to reveal such topological scales, two algorithms built around the idea of visualizing the evolution of different measured quantities are proposed. Then we test our algorithms on a few benchmark graphs whose community structures are already known. Numeric simulations are given to demonstrate the effectiveness and reliability of our methods.