The effect of generalized deactivation mechanism in weighted networks

In this paper, we propose a generalized deactivation model to characterize weighted networks. By introducing the special aging mechanism, the model can produce power-law distributions of degree, strength, and weight, as confirmed in many real networks. We also characterize the clustering and correlation properties of this class of networks. A scaling behavior of clustering coefficient C∼1/MC∼1/M is observed, where M refers to the number of active nodes. The generated network simultaneously exhibits hierarchical organization and disassortative degree correlation. All of these structural properties are confirmed by present empirical evidence.