Analysis of community structure in networks of correlated data
Physics and Society
2009-07-25 v2
Abstract
We present a reformulation of modularity that allows the analysis of the community structure in networks of correlated data. The new modularity preserves the probabilistic semantics of the original definition even when the network is directed, weighted, signed, and has self-loops. This is the most general condition one can find in the study of any network, in particular those defined from correlated data. We apply our results to a real network of correlated data between stores in the city of Lyon (France).
Cite
@article{arxiv.0812.3030,
title = {Analysis of community structure in networks of correlated data},
author = {Sergio Gomez and Pablo Jensen and Alex Arenas},
journal= {arXiv preprint arXiv:0812.3030},
year = {2009}
}
Comments
5 pages, 2 figures