Weighted Evolving Networks with Self-organized Communities  

作　　者：XIE Zhou LI Xiang WANG Xiao-Fan 

机构地区：[1]Lab of Complex Networks and Control, Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China [2]Department of Electronic Engineering, Fhdan University, Shanghai 200433, China

出　　处：《Communications in Theoretical Physics》2008年第7期261-266,共6页理论物理通讯（英文版）

基　　金：National Natural Science Foundation of China under Grant Nos.60504019 and 70431002

摘　　要：In order to describe the self-organization of communities in the evolution of weighted networks, we propose a new evolving model for weighted community-structured networks with the preferential mechanisms functioned in different levels according to community sizes and node strengths, respectively. Theoretical analyses and numerical simulations show that our model captures power-law distributions of community sizes, node strengths, and link weights, with tunable exponents of v ≥ 1, γ 〉 2, and α 〉 2, respectively, sharing large clustering coefficients and scaling clustering spectra, and covering the range from disassortative networks to assortative networks. Finally, we apply our new model to the scientific co-authorship networks with both their weighted and unweighted datasets to verify its effectiveness.

关 键 词：weighted network community structure preferential growth SCALE-FREE HIERARCHY 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]