Detecting overlapping community structure of complex networks in nature and society

Abstract

As the research of the complex network is becoming more and more hot in recent years, a lot of different characteristics have been found in the research of complex network, such as small-world property and scale-free properties. Community structure is one of the most relevant features of complex networks as well. Community, in which vertices are joined tightly together, between which there are only looser edges, exists in many real networks. Community detection is an important methodology for understanding the function and the organization of real-world networks. In this article, we arm to put forward a useful method to improve the efficiency and the validity of overlapping community detection. Such a measure can accurately detect community in both known network and standard synthetic network. Finally we apply our method to the real-world network whose community structure is known, and find that the results show high accuracy and efficiency.