Real growing networks such as the World Wide Web or personal connection based networks are characterized by a high degree of clustering, in addition to the small-world property and the absence of a characteristic scale. Appropriate modifications of the (Barabási-Albert) preferential attachment network growth capture all these aspects. We present a scaling theory to describe the behavior of the generalized models and the mean-field rate equation for clustering. This is solved for a specific case with the result C(k)∼1/k for the clustering of a node of degree k. This mean-field exponent agrees with simulations, and reproduces the clustering of many real networks.
%0 Journal Article
%1 Szabo2003Structural
%A Szabó, Gábor
%A Alava, Mikko
%A Kertész, János
%D 2003
%I American Physical Society
%J Physical Review E
%K scaling clustering scale-free-networks
%P 056102+
%R 10.1103/physreve.67.056102
%T Structural transitions in scale-free networks
%U http://dx.doi.org/10.1103/physreve.67.056102
%V 67
%X Real growing networks such as the World Wide Web or personal connection based networks are characterized by a high degree of clustering, in addition to the small-world property and the absence of a characteristic scale. Appropriate modifications of the (Barabási-Albert) preferential attachment network growth capture all these aspects. We present a scaling theory to describe the behavior of the generalized models and the mean-field rate equation for clustering. This is solved for a specific case with the result C(k)∼1/k for the clustering of a node of degree k. This mean-field exponent agrees with simulations, and reproduces the clustering of many real networks.
@article{Szabo2003Structural,
abstract = {{Real growing networks such as the World Wide Web or personal connection based networks are characterized by a high degree of clustering, in addition to the small-world property and the absence of a characteristic scale. Appropriate modifications of the (Barab\'{a}si-Albert) preferential attachment network growth capture all these aspects. We present a scaling theory to describe the behavior of the generalized models and the mean-field rate equation for clustering. This is solved for a specific case with the result C(k)∼1/k for the clustering of a node of degree k. This mean-field exponent agrees with simulations, and reproduces the clustering of many real networks.}},
added-at = {2019-06-10T14:53:09.000+0200},
author = {Szab\'{o}, G\'{a}bor and Alava, Mikko and Kert\'{e}sz, J\'{a}nos},
biburl = {https://www.bibsonomy.org/bibtex/2d93dd2bf0813698ae3ffe12b7a95112c/nonancourt},
citeulike-article-id = {10425179},
citeulike-linkout-0 = {http://dx.doi.org/10.1103/physreve.67.056102},
citeulike-linkout-1 = {http://link.aps.org/abstract/PRE/v67/i5/e056102},
citeulike-linkout-2 = {http://link.aps.org/pdf/PRE/v67/i5/e056102},
doi = {10.1103/physreve.67.056102},
interhash = {075e5a1a45a1d0311e59b36a6c3af72e},
intrahash = {d93dd2bf0813698ae3ffe12b7a95112c},
journal = {Physical Review E},
keywords = {scaling clustering scale-free-networks},
month = may,
pages = {056102+},
posted-at = {2012-03-07 14:42:26},
priority = {2},
publisher = {American Physical Society},
timestamp = {2019-08-01T16:13:16.000+0200},
title = {{Structural transitions in scale-free networks}},
url = {http://dx.doi.org/10.1103/physreve.67.056102},
volume = 67,
year = 2003
}