Evolving networks by merging cliques

Kazuhiro Takemoto and Chikoo Oosawa
Phys. Rev. E 72, 046116 – Published 17 October 2005

Abstract

We propose a model for evolving networks by merging building blocks represented as complete graphs, reminiscent of modules in biological system or communities in sociology. The model shows power-law degree distributions, power-law clustering spectra, and high average clustering coefficients independent of network size. The analytical solutions indicate that a degree exponent is determined by the ratio of the number of merging nodes to that of all nodes in the blocks, demonstrating that the exponent is tunable, and are also applicable when the blocks are classical networks such as Erdös-Rényi or regular graphs. Our model becomes the same model as the Barabási-Albert model under a specific condition.

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  • Received 23 May 2005

DOI:https://doi.org/10.1103/PhysRevE.72.046116

©2005 American Physical Society

Authors & Affiliations

Kazuhiro Takemoto*

  • Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka Fukuoka 820-8502, Japan

Chikoo Oosawa

  • Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka Fukuoka 820-8502, Japan and Bioalgrithm Project, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology, Iizuka Fukuoka 820-8502, Japan

  • *Electronic address: d673050k@bio.kyutech.ac.jp
  • Electronic address: chikoo@bio.kyutech.ac.jp

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Issue

Vol. 72, Iss. 4 — October 2005

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