Detect overlapping and hierarchical community structure in networks
Huawei Shen, Xueqi Cheng, Kai Cai, Mao-Bin Hu

TL;DR
This paper introduces EAGLE, an algorithm that simultaneously detects overlapping and hierarchical community structures in networks using maximal cliques and an extended modularity measure.
Contribution
The paper presents a novel algorithm that integrates detection of overlapping and hierarchical communities in networks within a unified framework.
Findings
EAGLE effectively detects overlapping communities.
The method reveals hierarchical community structures.
Applications to real networks show excellent results.
Abstract
Clustering and community structure is crucial for many network systems and the related dynamic processes. It has been shown that communities are usually overlapping and hierarchical. However, previous methods investigate these two properties of community structure separately. This paper proposes an algorithm (EAGLE) to detect both the overlapping and hierarchical properties of complex community structure together. This algorithm deals with the set of maximal cliques and adopts an agglomerative framework. The quality function of modularity is extended to evaluate the goodness of a cover. The examples of application to real world networks give excellent results.
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