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)∼ l/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 Szabo:2003p4317
%A Szabó, G
%A Alava, M
%A Kertész, J
%D 2003
%J Phys Rev E
%K imported
%N 5
%P 056102
%T Structural transitions in scale-free networks
%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)∼ l/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{Szabo:2003p4317,
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)∼ l/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 = {2009-02-08T16:38:56.000+0100},
author = {Szab{\'o}, G and Alava, M and Kert{\'e}sz, J},
biburl = {https://www.bibsonomy.org/bibtex/215a18438930259bd22631d36d2f82d45/svsegbro},
date-added = {2008-07-10 17:13:50 +0200},
date-modified = {2008-08-08 17:08:52 +0200},
interhash = {075e5a1a45a1d0311e59b36a6c3af72e},
intrahash = {15a18438930259bd22631d36d2f82d45},
journal = {Phys Rev E},
keywords = {imported},
local-url = {file://localhost/Users/sven/Documents/Papers/2003/Szab%C3%B3/Phys%20Rev%20E%202003%20Szab%C3%B3.pdf},
number = 5,
pages = 056102,
rating = {0},
read = {Yes},
timestamp = {2009-02-08T16:38:57.000+0100},
title = {Structural transitions in scale-free networks},
uri = {papers://B7B184F3-8CE5-4C43-B61C-B7952DE67982/Paper/p4317},
volume = 67,
year = 2003
}