Abstract
Many social, biological or technological systems are recognized as complex networks with assortative or disassortative mixing pattern, which is lacking in typical theorical network models, such as, Watts-Strogatz small-world model or Barabási-Albert scale-free network. In this paper, we propose a mechanism which models the emergence of the degree correlation property of complex networks. Numerical simulations indicate that this correlation-adjustable network model can exhibit fundamentally different degree correlation mixing patterns with a scale-free degree sequence. Moreover, the structural properties of networks, such as the average path length and clustering property are also investigated.
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