Increasingly, methods to identify community structure in networks have been proposed which allow groups to overlap. These methods have taken a variety of forms, resulting in a lack...
Mark K. Goldberg, Stephen Kelley, Malik Magdon-Ism...
Abstract--We propose a framework for discovery of collaborative community structure in Wiki-based knowledge repositories based on raw-content generation analysis. We leverage topic...
Petko Bogdanov, Nicholas D. Larusso, Ambuj K. Sing...
Social networks have small-world property, hierarchical community structure, and some other properties. This paper proposes models of networks with these properties and algorithm ...
Spectral analysis has been successfully applied to the detection of community structure of networks, respectively being based on the adjacency matrix, the standard Laplacian matrix...
Abstract. Modularity was introduced as a measure of goodness for the community structure induced by a partition of the set of vertices in a graph. Then, it also became an objective...
The discovery of community structure in a large number of complex networks has attracted lots of interest in recent years. One category of algorithms for detecting community struct...
In this paper, we propose a new network growth model and its learning algorithm to more precisely model such a real-world growing network as the Web. Unlike the conventional model...
Abstract--As research into community finding in social networks progresses, there is a need for algorithms capable of detecting overlapping community structure. Many algorithms hav...
This paper addresses the issue of emergence of robust cooperation among self-interested agents interacting in N-player social dilemma games. A series of graphs are created each ex...
Complex network analysis is a growing research area in a wide variety of domains and has recently become closely associated with data, text and web mining. One of the most active ...
Cristian Klen dos Santos, Alexandre Evsukoff, Beat...