Hub-Based Community Finding
arXiv:cond-mat/0405022
Abstract
This article presents a hub-based approach to community finding in complex networks. After identifying the network nodes with highest degree (the so-called hubs), the network is flooded with wavefronts of labels emanating from the hubs, accounting for the identification of the involved communities. The simplicity and potential of this method, which is presented for direct/undirected and weighted/unweighted networks, is illustrated with respect to the Zachary karate club data, image segmentation, and concept association. Attention is also given to the identification of the boundaries between communities.
4 pages, 3 figures, 1 table
Cited by in corpus (7)
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- Computing communities in large networks using random walks (long version)
- Communities as Well Separated Subgraphs With Cohesive Cores: Identification of Core-Periphery Structures in Link Communities