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Evolution Mechanisms of Weighted Complex networks : Growth and Reinforcement

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Abstract Book of the XXIII IUPAP International Conference on Statistical Physics, Genova, Italy, (9-13 July 2007)

Abstract

Network evolution is a key issue of network study to understand design principle underlying network organization . We investigate the evolution mechanisms of weighted networks by analyzing time-dependent data of real weighted networks. We find power-law growth rates of networks and identify generalized kernel functions which drive network evolution. Based on observed results, we propose an evolving weighted network model. Our model successfully reproduce strength, degree and weight distributions of real networks. In addition, we study weight-topology correlations in model and real weighted networks.

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