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Characterizing core–periphery structure of complex network by h-core and fingerprint curve

Author

Listed:
  • Li, Simon S.
  • Ye, Adam Y.
  • Qi, Eric P.
  • Stanley, H. Eugene
  • Ye, Fred Y.

Abstract

It is proposed that the core–periphery structure of complex networks can be simulated by h-cores and fingerprint curves. While the features of core structure are characterized by h-core, the features of periphery structure are visualized by rose or spiral curve as the fingerprint curve linking to entire-network parameters. It is suggested that a complex network can be approached by h-core and rose curves as the first-order Fourier-approach, where the core–periphery structure is characterized by five parameters: network h-index, network radius, degree power, network density and average clustering coefficient. The simulation looks Fourier-like analysis.

Suggested Citation

  • Li, Simon S. & Ye, Adam Y. & Qi, Eric P. & Stanley, H. Eugene & Ye, Fred Y., 2018. "Characterizing core–periphery structure of complex network by h-core and fingerprint curve," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1206-1215.
    • Handle: RePEc:eee:phsmap:v:492:y:2018:i:c:p:1206-1215
    DOI: 10.1016/j.physa.2017.11.048
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    Cited by:

    1. Wei, Shelia X. & Tong, Tong & Rousseau, Ronald & Wang, Wanru & Ye, Fred Y., 2022. "Relations among the h-, g-, ψ-, and p-index and offset-ability," Journal of Informetrics, Elsevier, vol. 16(4).

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