Rank-based model for weighted network with hierarchical organization and disassortative mixing

L. Tian*, D. N. Shi

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

5 Citations (Scopus)


In this paper, we study a rank-based model for weighted network. The evolution rule of the network is based on the ranking of node strength, which couples the topological growth and the weight dynamics. Analytically and by simulations, we demonstrate that the generated networks recover the scale-free distributions of degree and strength in the whole region of the growth dynamics parameter (α>0). Moreover, this network evolution mechanism can also produce scale-free property of weight, which adds deeper comprehension of the networks growth in the presence of incomplete information. We also characterize the clustering and correlation properties of this class of networks. It is showed that at α=1 a structural phase transition occurs, and for α>1 the generated network simultaneously exhibits hierarchical organization and disassortative degree correlation, which is consistent with a wide range of biological networks.

Original languageEnglish
Pages (from-to)167-171
Number of pages5
JournalEuropean Physical Journal B
Issue number2
Publication statusPublished - 12 Apr 2007

Scopus Subject Areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics


Dive into the research topics of 'Rank-based model for weighted network with hierarchical organization and disassortative mixing'. Together they form a unique fingerprint.

Cite this