Weighted assortative and disassortative networks model

C.C. Leung and H.F. Chau

Physica A: Statistical Mechanics and its Applications, 2007, vol. 378, issue 2, 591-602

Abstract: Real-world networks process structured connections since they have non-trivial vertex degree correlation and clustering. Here we propose a toy model of structure formation in real-world weighted network. In our model, a network evolves by topological growth as well as by weight change. In addition, we introduce the weighted assortativity coefficient, which generalizes the assortativity coefficient of a topological network, to measure the tendency of having a high-weighted link between two vertices of similar degrees. Network generated by our model exhibits scale-free behavior with a tunable exponent. Besides, a few non-trivial features found in real-world networks are reproduced by varying the parameter ruling the speed of weight evolution. Most importantly, by studying the weighted assortativity coefficient, we found that both topologically assortative and disassortative networks generated by our model are in fact weighted assortative.

Keywords: Assortative and disassortative networks; Clustering; Evolving weighted network; Mean field approximation; Weighted assortativity coefficient (search for similar items in EconPapers)
Date: 2007
References: View complete reference list from CitEc
Citations: View citations in EconPapers (20)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:378:y:2007:i:2:p:591-602

DOI: 10.1016/j.physa.2006.12.022

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