Tian Liang, Zhu Chen-Ping, Shi Da-Ning, Gu Zhi-Ming, Zhou Tao
College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, People's Republic of China.
Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Oct;74(4 Pt 2):046103. doi: 10.1103/PhysRevE.74.046103. Epub 2006 Oct 4.
We propose a model of network growth that generalizes the deactivation model previously suggested for complex networks. Several topological features of this generalized model, such as the degree distribution and clustering coefficient, have been investigated analytically and by simulations. A scaling behavior of clustering coefficient C approximately 1/M is theoretically obtained, where M refers to the number of active nodes in the network. We discuss the relationship between the recently observed numerical behavior of clustering coefficient in the coauthor and paper citation networks and our theoretical result. It shows that both of them are induced by deactivation mechanism. By introducing a perturbation, the generated network undergoes a transition from large to small world, meanwhile the scaling behavior of C is conserved. It indicates that C approximately 1/M is a universal scaling behavior induced by deactivation mechanism.
我们提出了一种网络增长模型，该模型推广了先前针对复杂网络提出的失活模型。已通过解析和模拟研究了此广义模型的几个拓扑特征，例如度分布和聚类系数。理论上得到了聚类系数C约为1/M的标度行为，其中M指网络中活跃节点的数量。我们讨论了合著者网络和论文引用网络中最近观察到的聚类系数数值行为与我们的理论结果之间的关系。结果表明，它们两者都是由失活机制引起的。通过引入扰动，生成的网络经历从大到小世界的转变，同时C的标度行为得以保留。这表明C约为1/M是由失活机制引起的通用标度行为。
