Highly clustered scale-free networks

Konstantin Klemm and Víctor M. Eguíluz
Phys. Rev. E 65, 036123 – Published 21 February 2002
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We propose a model for growing networks based on a finite memory of the nodes. The model shows stylized features of real-world networks: power-law distribution of degree, linear preferential attachment of new links, and a negative correlation between the age of a node and its link attachment rate. Notably, the degree distribution is conserved even though only the most recently grown part of the network is considered. As the network grows, the clustering reaches an asymptotic value larger than that for regular lattices of the same average connectivity and similar to the one observed in the networks of movie actors, coauthorship in science, and word synonyms. These highly clustered scale-free networks indicate that memory effects are crucial for a correct description of the dynamics of growing networks.

  • Received 28 August 2001


©2002 American Physical Society

Authors & Affiliations

Konstantin Klemm1,* and Víctor M. Eguíluz1,2,3,†

  • 1Center for Chaos and Turbulence Studies, Niels Bohr Institute, Blegdamsvej 17, DK-2100 Copenhagen Ø, Denmark
  • 2Instituto Mediterráneo de Estudios Avanzados IMEDEA (CSIC-UIB), E07071 Palma de Mallorca, Spain
  • 3Departamento de Física, Universidad de las Islas Baleares, E07071 Palma de Mallorca, Spain

  • *Email address: klemm@nbi.dk
  • Email address: victor@imedea.uib.dk

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Vol. 65, Iss. 3 — March 2002

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