We derive the finite-size dependence of the clustering coefficient of scale-free random graphs generated by the configuration model with degree distribution exponent 2<γ<3. Degree heterogeneity increases the presence of triangles in the network up to levels that compare to those found in many real networks even for extremely large nets. We also find that for values of γ≈2, clustering is virtually size independent and, at the same time, becomes a de facto non-self-averaging topological property. This implies that a single-instance network is not representative of the ensemble even for very large network sizes.
%0 Journal Article
%1 ColomerdeSimon2012Clustering
%A Colomer-de Simón, Pol
%A Bogu\ ná, Marián
%D 2012
%I American Physical Society
%J Physical Review E
%K clustering scale-free-networks finite-size
%P 026120+
%R 10.1103/physreve.86.026120
%T Clustering of random scale-free networks
%U http://dx.doi.org/10.1103/physreve.86.026120
%V 86
%X We derive the finite-size dependence of the clustering coefficient of scale-free random graphs generated by the configuration model with degree distribution exponent 2<γ<3. Degree heterogeneity increases the presence of triangles in the network up to levels that compare to those found in many real networks even for extremely large nets. We also find that for values of γ≈2, clustering is virtually size independent and, at the same time, becomes a de facto non-self-averaging topological property. This implies that a single-instance network is not representative of the ensemble even for very large network sizes.
@article{ColomerdeSimon2012Clustering,
abstract = {{We derive the finite-size dependence of the clustering coefficient of scale-free random graphs generated by the configuration model with degree distribution exponent 2<γ<3. Degree heterogeneity increases the presence of triangles in the network up to levels that compare to those found in many real networks even for extremely large nets. We also find that for values of γ≈2, clustering is virtually size independent and, at the same time, becomes a de facto non-self-averaging topological property. This implies that a single-instance network is not representative of the ensemble even for very large network sizes.}},
added-at = {2019-06-10T14:53:09.000+0200},
author = {Colomer-de Sim\'{o}n, Pol and Bogu\ {n}\'{a}, Mari\'{a}n},
biburl = {https://www.bibsonomy.org/bibtex/2004e3c446a8d4e1a2fe4a73c7f97f207/nonancourt},
citeulike-article-id = {11158078},
citeulike-linkout-0 = {http://dx.doi.org/10.1103/physreve.86.026120},
citeulike-linkout-1 = {http://link.aps.org/abstract/PRE/v86/i2/e026120},
citeulike-linkout-2 = {http://link.aps.org/pdf/PRE/v86/i2/e026120},
doi = {10.1103/physreve.86.026120},
interhash = {28daaf67681018781a3e71fa3314a702},
intrahash = {004e3c446a8d4e1a2fe4a73c7f97f207},
journal = {Physical Review E},
keywords = {clustering scale-free-networks finite-size},
month = aug,
pages = {026120+},
posted-at = {2012-08-30 18:21:25},
priority = {2},
publisher = {American Physical Society},
timestamp = {2019-08-01T16:16:40.000+0200},
title = {{Clustering of random scale-free networks}},
url = {http://dx.doi.org/10.1103/physreve.86.026120},
volume = 86,
year = 2012
}