A Mutual Attraction Model for Both Assortative and Disassortative Weighted Networks

Abstract

In most networks, the connection between a pair of nodes is the result of their mutual affinity and attachment. In this letter, we will propose a Mutual Attraction Model to characterize weighted evolving networks. By introducing the initial attractiveness $A$ and the general mechanism of mutual attraction (controlled by parameter $m$), the model can naturally reproduce scale-free distributions of degree, weight and strength, as found in many real systems. Simulation results are in consistent with theoretical predictions. Interestingly, we also obtain nontrivial clustering coefficient C and tunable degree assortativity r, depending on $m$ and A. Our weighted model appears as the first one that unifies the characterization of both assortative and disassortative weighted networks.

4 pages, 3 figures

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Cited by in corpus (6)

• Evolving Apollonian Networks with Small-world Scale-free topologies
• Uncovering the topology of configuration space networks
• Analysis and perturbation of degree correlation in complex networks
• Rank-based model for weighted network with hierarchical organization and disassortative mixing
• Analytic Solution to Clustering Coefficients on Weighted Networks
• A Survey of Evolving Models for Weighted Complex Networks based on their Dynamics and Evolution