Identifying the community structure in a complex network has been addressed in many different ways. In this paper, the simulated annealing strategy is used to maximize the modularity of a network, associating with a dissimilarity-index-based and with a diffusion-distance-based k-means iterative...

Many complex systems can be represented as complex networks. Among them there has been much interest on community structure recently, and many studies focus attention on it, in particular community detection. While community detection can provide us much information, the community structure...

Community structure is a common phenomenon in complex networks, and it has been shown that some communities in complex networks often overlap each other. So in this paper we propose a new algorithm to detect overlapping community structure in complex networks. To identify the overlapping...

In this paper, we present a new approach to extract communities in the complex networks with considerable accuracy. We introduce the core-vertex and the intimate degree between the community and its neighboring vertices. First, we find the core-vertices as the initial community. These...

Complex technological networks represent a growing challenge to support and maintain as their number of elements become higher and their interdependencies more involved. On the other hand, for networks that grow in a decentralized manner, it is possible to observe certain patterns in their...

In this paper, we propose a novel measure that integrates both the concept of closed walks and clustering coefficients to replace the edge betweenness in the well-known divisive hierarchical clustering algorithm, the Girvan and Newman method (GN). The edges with the lowest value are removed...

Based on a database of collaboration recording in econophysics scientists and other networks, hierarchical clustering method and the algorithm of Girvan and Newman are applied to detect their community structure. The interesting results for community structure of econophysicists collaboration...

Community structure is an important property of complex networks. How to detect the communities is significant for understanding the network structure and to analyze the network properties. Many algorithms, such as K–L and GN, have been proposed to detect community structures in complex...

Community detection is a topic of considerable recent interest within complex networks, but most methods proposed so far are divisive and agglomerative methods which delete only one edge each time to split the network, or agglomerating only one node each time until no individual node remains....