Community detection is a very important problem in social network analysis. Classical clustering approach, K-means, has been shown to be very efficient to detect communities in networks. However, K-means is quite sensitive to the initial centroids or seeds, especially when it is used to detect...

We show here that the problem of maximizing a family of quantitative functions, encompassing both the modularity (Q-measure) and modularity density (D-measure), for community detection can be uniformly understood as a combinatoric optimization involving the trace of a matrix called modularity...

Most community detection methods use network topology and edge density to identify optimal communities. However, in these methods, several objects that are connected by high weights may be decomposed into different communities, even when they intuitively belong to a single community. In this...

In this paper, a unique algorithm is proposed to detect overlapping communities in the un-weighted and weighted networks with considerable accuracy. The maximal cliques, overlapping vertex, bridge vertex and isolated vertex are introduced. First, all the maximal cliques are extracted by the...

We investigate the networks of committee and subcommittee assignments in the United States House of Representatives from the 101st–108th Congresses, with the committees connected by “interlocks” or common membership. We examine the community structure in these networks using several...

Various evolving approaches have been extensively applied to evolve densely connected communities in complex networks. However these techniques have been primarily single objective optimization techniques, which optimize only a specific feature of the network missing on other important features....

In the last decade, the problem of community detection in complex networks has attracted the attention of many researchers in many domains, several methods and algorithms have been proposed to deal with this problem, many of them consider it as an optimization problem and various bio-inspired...

This article describes how parallel to the continuous growth of the Internet, which allows people to share and collaborate more, social networks have become more attractive as a research topic in many different disciplines. Community structures are established upon interactions between people....

Migration has become a prominent research theme in geography and regional science and it has been approached from various methodological angles. Nonetheless, a common missing element in most migration studies is the lack of awareness of the overall network topology, which characterizes migration...

This paper studies international migration from a complex-network perspective. We define the international-migration network (IMN) as the weighted-directed graph where nodes are world countries and links account for the stock of migrants originated in a given country and living in another...