Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
IMPROVED CLUSTERING THROUGH HETEROGENEITY IN PREFERENTIAL ATTACHMENT NETWORKS
Year:2009
Research Areas
  • Mathematics,
  • Electronic
Information
Abstract
In this paper we present a study of the influence of heterogeneity on the clustering of preferential attachment networks. The study is performed by the numerical analysis of the threshold preferential attachment model, a generalization of the Barab¿asi¿Albert model to heterogeneous complex networks. Heterogeneous networks are characterized by the existence of intrinsic properties of the nodes which induce specific affinities in their interactions. We analyze the influence of the affinity parameters on the distribution of degree-averaged clustering coefficients of the threshold model. We show that the introduction of heterogeneity increases the inverse correlation between clustering and connectivity of the nodes, inducing a power-law scaling in the clustering distribution. We also show that a higher level of heterogeneity increases the overall clustering coefficients irrespective of the node degrees. These results exhibit a better agreement of the extended model with the empirical observations of clustering in real networks.
International
Si
JCR
Si
Title
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
ISBN
0218-1274
Impact factor JCR
0,87
Impact info
Volume
19
10.1142/S0218127409023445
Journal number
3
From page
1029
To page
1036
Month
MARZO
Ranking
Participants
  • Autor: Antonio Santiago Andrés (UPM)
  • Autor: Rosa Maria Benito Zafrilla (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Sistemas Complejos
  • Departamento: Física y Mecánica Fundamentales y Aplicada a la Ingeniería Agroforestal
S2i 2019 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
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