Fast Community Identification by Hierarchical Growth
Physics and Society
2009-11-11 v1 Disordered Systems and Neural Networks
Computational Physics
Abstract
A new method for community identification is proposed which is founded on the analysis of successive neighborhoods, reached through hierarchical growth from a starting vertex, and on the definition of communities as a subgraph whose number of inner connections is larger than outer connections. In order to determine the precision and speed of the method, it is compared with one of the most popular community identification approaches, namely Girvan and Newman's algorithm. Although the hierarchical growth method is not as precise as Girvan and Newman's method, it is potentially faster than most community finding algorithms.
Keywords
Cite
@article{arxiv.physics/0602144,
title = {Fast Community Identification by Hierarchical Growth},
author = {Francisco A. Rodrigues and Gonzalo Travieso and Luciano da F. Costa},
journal= {arXiv preprint arXiv:physics/0602144},
year = {2009}
}
Comments
6 pages, 5 figures