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A Mutual Attraction Model for Both Assortative and Disassortative Weighted Networks
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 and the general mechanism of mutual attraction
(controlled by parameter ), 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 and A. Our weighted model appears as
the first one that unifies the characterization of both assortative and
disassortative weighted networks.Comment: 4 pages, 3 figure
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