English

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.

Keywords

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