Universal scaling of distances in complex networks
Disordered Systems and Neural Networks
2009-11-10 v2 Statistical Mechanics
Abstract
Universal scaling of distances between vertices of Erdos-Renyi random graphs, scale-free Barabasi-Albert models, science collaboration networks, biological networks, Internet Autonomous Systems and public transport networks are observed. A mean distance between two nodes of degrees k_i and k_j equals to <l_{ij}>=A-B log(k_i k_j). The scaling is valid over several decades. A simple theory for the appearance of this scaling is presented. Parameters A and B depend on the mean value of a node degree <k>_nn calculated for the nearest neighbors and on network clustering coefficients.
Cite
@article{arxiv.cond-mat/0411160,
title = {Universal scaling of distances in complex networks},
author = {Janusz A. Holyst and Julian Sienkiewicz and Agata Fronczak and Piotr Fronczak and Krzysztof Suchecki},
journal= {arXiv preprint arXiv:cond-mat/0411160},
year = {2009}
}
Comments
4 pages, 3 figures, 1 table