Rank-dependent deactivation in network evolution

Details Rank-dependent deactivation in network evolution Rank-dependent deactivation in network evolution

2009-12-08

arxiv.org/abs/0912.1400v1

PHYSICAL REVIEW E 80, 066105 (2009)

Physics

Physics and Society

5 pages, 5 figures, RevTex4

Scientific paper

A rank-dependent deactivation mechanism is introduced to network evolution. The growth dynamics of the network is based on a finite memory of individuals, which is implemented by deactivating one site at each time step. The model shows striking features of a wide range of real-world networks: power-law degree distribution, high clustering coefficient, and disassortative degree correlation.

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