We study community structure of networks. We have developed a scheme for maximizing the modularity Q [Newman and Girvan, Phys. Rev. E 69, 026113 (2004)] based on mean field methods. Further, we have defined a simple family of random networks with community structure; we understand the behavior of these networks analytically. Using these networks, we show how the mean field methods display better performance than previously known deterministic methods for optimization of Q
Networks capture pairwise interactions between entities and are frequently used in applications such...
Networks capture pairwise interactions between entities and are frequently used in applications such...
In many networks, it is of great interest to identify communities, unusually densely knit groups of ...
We study community structure of networks. We have developed a scheme for maximizing the modularity Q...
Abstract—Many networks including social networks, computer networks, and biological networks are fou...
We reformulate the problem of modularity maximization over the set of partitions of a network as a c...
Abstract. We reformulate the problem of modularity maximization over the set of partitions of a netw...
Networks constitute powerful means of representing various types of complex systems, where nodes den...
Networks constitute powerful means of representing various types of complex systems, where nodes den...
Characterizing large-scale organization in networks, including multilayer networks, is one of the mo...
Characterizing large-scale organization in networks, including multilayer networks, is one of the mo...
In this paper, we first discuss the definition of modularity (Q) used as a metric for community qual...
Networks capture pairwise interactions between entities and are frequently used in applications such...
Many social networks and complex systems are found to be naturally divided into clusters of densely ...
Abstract—Many networks, indifferent of their function and scope, converge to a scale-free architectu...
Networks capture pairwise interactions between entities and are frequently used in applications such...
Networks capture pairwise interactions between entities and are frequently used in applications such...
In many networks, it is of great interest to identify communities, unusually densely knit groups of ...
We study community structure of networks. We have developed a scheme for maximizing the modularity Q...
Abstract—Many networks including social networks, computer networks, and biological networks are fou...
We reformulate the problem of modularity maximization over the set of partitions of a network as a c...
Abstract. We reformulate the problem of modularity maximization over the set of partitions of a netw...
Networks constitute powerful means of representing various types of complex systems, where nodes den...
Networks constitute powerful means of representing various types of complex systems, where nodes den...
Characterizing large-scale organization in networks, including multilayer networks, is one of the mo...
Characterizing large-scale organization in networks, including multilayer networks, is one of the mo...
In this paper, we first discuss the definition of modularity (Q) used as a metric for community qual...
Networks capture pairwise interactions between entities and are frequently used in applications such...
Many social networks and complex systems are found to be naturally divided into clusters of densely ...
Abstract—Many networks, indifferent of their function and scope, converge to a scale-free architectu...
Networks capture pairwise interactions between entities and are frequently used in applications such...
Networks capture pairwise interactions between entities and are frequently used in applications such...
In many networks, it is of great interest to identify communities, unusually densely knit groups of ...