Weighted Evolving Networks with Self-organized Communities |
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Authors: | XIE Zhou LI Xiang WANG Xiao-Fan |
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Institution: | 1. Lab of Complex Networks and Control, Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
;2. Department of Electronic Engineering, Fudan University, Shanghai 200433, China |
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Abstract: | 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 ν≥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. |
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Keywords: | weighted network community structure preferential growth scale-free hierarchy |
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