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Gaining scale-free and high clustering complex networks

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  • Bu, Shouliang
  • Wang, Bing-Hong
  • Zhou, Tao

Abstract

By making use of two observing facts for many natural and social networks, i.e., the nodes’ diversity, and the disassortative (or assortative) properties for biological and technological (or social) networks, a simple and elegant model with three kinds of nodes and deterministic selective linking rule is proposed in this paper. We show that the given model can successfully capture two generic topological properties of many real networks: they are scale-free and they display a high degree of clustering. In practice, most models proposed to describe the topology of complex networks have difficulty to capture simultaneously these two features.

Suggested Citation

  • Bu, Shouliang & Wang, Bing-Hong & Zhou, Tao, 2007. "Gaining scale-free and high clustering complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(2), pages 864-868.
    • Handle: RePEc:eee:phsmap:v:374:y:2007:i:2:p:864-868
    DOI: 10.1016/j.physa.2006.08.048
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    References listed on IDEAS

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    1. S. Redner, 1998. "How popular is your paper? An empirical study of the citation distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 4(2), pages 131-134, July.
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    Keywords

    Complex networks; Scale-free;

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