We consider the problem of finding communities or modules in directed networks. In the past, the most common approach to this problem has been to ignore edge direction and apply methods developed for community discovery in undirected networks, but this approach discards potentially useful information contained in the edge directions. Here we show how the widely used community finding technique of modularity maximization can be generalized in a principled fashion to incorporate information contained in edge directions. We describe an explicit algorithm based on spectral optimization of the modularity and show that it gives demonstrably better results than previous methods on a variety of test networks, both real and computer generated
Abstract Background The detection of modules or community structure is widely used to reveal the und...
Abstract—In this paper we present a novel strategy to discover the community structure of (possibly,...
We consider the problem of detecting communities or modules in networks, groups of vertices with a h...
We consider the problem of finding communities or modules in directed networks. In the past, the mos...
Abstract. The most common approach to community identification of directed networks has been to igno...
To identify communities in directed networks, we propose a generalized form of modularity in directe...
Networks constitute powerful means of representing various types of complex systems, where nodes den...
In this paper we consider the community detection problem from two different perspectives. We first ...
Part 5: Natural Language ProcessingInternational audienceExisting studies about community detection ...
Community detection in bipartite networks is a popular topic. Two widely used methods to capture com...
Some temporal networks, most notably citation networks, are naturally represented as directed acycli...
Modularity maximization has been one of the most widely used approaches in the last decade for disco...
AbstractFinding communities in networks is a commonly used form of network analysis. There is a myri...
The community structure of a complex network can be determined by finding the partitioning of its n...
Networks are a widely used tool for investigating the large-scale connectivity structure in complex ...
Abstract Background The detection of modules or community structure is widely used to reveal the und...
Abstract—In this paper we present a novel strategy to discover the community structure of (possibly,...
We consider the problem of detecting communities or modules in networks, groups of vertices with a h...
We consider the problem of finding communities or modules in directed networks. In the past, the mos...
Abstract. The most common approach to community identification of directed networks has been to igno...
To identify communities in directed networks, we propose a generalized form of modularity in directe...
Networks constitute powerful means of representing various types of complex systems, where nodes den...
In this paper we consider the community detection problem from two different perspectives. We first ...
Part 5: Natural Language ProcessingInternational audienceExisting studies about community detection ...
Community detection in bipartite networks is a popular topic. Two widely used methods to capture com...
Some temporal networks, most notably citation networks, are naturally represented as directed acycli...
Modularity maximization has been one of the most widely used approaches in the last decade for disco...
AbstractFinding communities in networks is a commonly used form of network analysis. There is a myri...
The community structure of a complex network can be determined by finding the partitioning of its n...
Networks are a widely used tool for investigating the large-scale connectivity structure in complex ...
Abstract Background The detection of modules or community structure is widely used to reveal the und...
Abstract—In this paper we present a novel strategy to discover the community structure of (possibly,...
We consider the problem of detecting communities or modules in networks, groups of vertices with a h...