Higher order clustering coefficients in Barabási–Albert networks

Agata Fronczak, Janusz A Hołyst, Maciej Jedynak and Julian Sienkiewicz

Physica A: Statistical Mechanics and its Applications, 2002, vol. 316, issue 1, 688-694

Abstract: Higher order clustering coefficients C(x) are introduced for random networks. The coefficients express probabilities that the shortest distance between any two nearest neighbours of a certain vertex i equals x, when one neglects all paths crossing the node i. Using C(x) we found that in the Barabási–Albert (BA) model the average shortest path length in a node's neighbourhood is smaller than the equivalent quantity of the whole network and the remainder depends only on the network parameter m. Our results show that small values of the standard clustering coefficient in large BA networks are due to random character of the nearest neighbourhood of vertices in such networks.

Keywords: Disordered systems; Scale-free networks; Computer simulations (search for similar items in EconPapers)
Date: 2002
References: View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:316:y:2002:i:1:p:688-694

DOI: 10.1016/S0378-4371(02)01336-5

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