Scaling of distances in correlated complex networks

Janusz A. Hołyst, Julian Sienkiewicz, Agata Fronczak, Piotr Fronczak and Krzysztof Suchecki

Physica A: Statistical Mechanics and its Applications, 2005, vol. 351, issue 1, 167-174

Abstract: The influence of node–node degree correlations on distances in complex networks has been studied. We have found that even the presence of strong correlations in complex networks does not break a universal scaling of distances between vertices of such networks as science collaboration networks, biological networks, Internet Autonomous Systems and public transport systems. A mean distance between two nodes of degrees ki and kj in such networks equals to 〈lij〉=A-Blog(kikj) for a fixed value of the product kikj. The scaling is valid over several decades. Parameters A and B depend on the mean value of a node degree 〈k〉nn calculated for the nearest neighbors. We have found that extending our simple theory basing on a random branching tree by the first-order node degree correlations improves theoretical predictions for parameters A and B in assortative networks, while it fails in disassortative ones.

Keywords: Complex networks; Distances; Scaling; Correlations (search for similar items in EconPapers)
Date: 2005
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:351:y:2005:i:1:p:167-174

DOI: 10.1016/j.physa.2004.12.018

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