Universal scaling behavior of clustering coefficient induced by deactivation mechanism

Liang Tian, Chen Ping Zhu*, Da Ning Shi*, Zhi Ming Gu, Tao Zhou

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

19 Citations (Scopus)


We propose a model of network growth that generalizes the deactivation model previously suggested for complex networks. Several topological features of this generalized model, such as the degree distribution and clustering coefficient, have been investigated analytically and by simulations. A scaling behavior of clustering coefficient Câ 1â •M is theoretically obtained, where M refers to the number of active nodes in the network. We discuss the relationship between the recently observed numerical behavior of clustering coefficient in the coauthor and paper citation networks and our theoretical result. It shows that both of them are induced by deactivation mechanism. By introducing a perturbation, the generated network undergoes a transition from large to small world, meanwhile the scaling behavior of C is conserved. It indicates that Câ 1â •M is a universal scaling behavior induced by deactivation mechanism.

Original languageEnglish
Article number046103
JournalPhysical Review E
Issue number4
Publication statusPublished - Oct 2006

Scopus Subject Areas

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics


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