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Organizations of rich nodes in complex networks

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  • Zhao, H.
  • Gao, Z.Y.

Abstract

Hidden regularities of complex networks may be different from the properties they show to us externally. In this paper, organization of rich nodes in real world and model networks are investigated. It is found that in scale-free networks, when the rich level is relatively low, the degree distribution of rich nodes follows a power law. On the transitivity and mixing pattern, the clustering coefficient C and assortativity coefficient r of rich nodes fluctuate with the increment of rich level ρ in World Wide Web, while in protein–protein Interaction network, a scaling law can be observed in describing the clustering coefficient C of rich nodes as a function of the rich level and an extremum can be expected in the assortativity of rich nodes at a specified rich level. Furthermore, both positive and negative assortativity coefficient can be observed in different rich levels in the studied real world networks, which dedicates that the rich nodes may be organized different from the networks of their own.

Suggested Citation

  • Zhao, H. & Gao, Z.Y., 2007. "Organizations of rich nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 473-481.
    • Handle: RePEc:eee:phsmap:v:381:y:2007:i:c:p:473-481
    DOI: 10.1016/j.physa.2007.03.016
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    References listed on IDEAS

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    1. Dorogovtsev, S.N. & Mendes, J.F.F., 2003. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780198515906.
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    Cited by:

    1. Dong, Gaogao & Tian, Lixin & Du, Ruijin & Fu, Min & Stanley, H. Eugene, 2014. "Analysis of percolation behaviors of clustered networks with partial support–dependence relations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 370-378.

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