Abstract

We present a general model for the growth of weighted networks in which the structural growth is coupled with the edges' weight dynamical evolution. The model is based on a simple weight-driven dynamics and a weights' reinforcement mechanism coupled to the local network growth. That coupling can be generalized in order to include the effect of additional randomness and nonlinearities which can be present in real-world networks. The model generates weighted graphs exhibiting the statistical properties observed in several real-world systems. In particular, the model yields a nontrivial time evolution of vertices' properties and scale-free behavior with exponents depending on the microscopic parameters characterizing the coupling rules. Very interestingly, the generated graphs spontaneously achieve a complex hierarchical architecture characterized by clustering and connectivity correlations varying as a function of the vertices' degree.

Notes

Originally published in Physical Review E, v.70 no.6 (2004), 66149. DOI:10.1103/PhysRevE.70.066149. Dr. Vespignani is affiliated with Northeastern University as of the time of deposit.

Keywords

weighted networks, clustering, structural growth, dynamical evolution

Subject Categories

Information modeling

Disciplines

Physics

Publisher

American Physical Society

Publication Date

12-1-2004

Rights Information

©2004 American Physical Society

Rights Holder

American Physical Society

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