Random Graphs with Clustering
Random Graphs with Clustering
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DOI：
10.1103/physrevlett.103.058701
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发表时间：
2009-07-31
影响因子：
8.6
通讯作者：
Newman, M. E. J.
中科院分区：
文献类型：
--
作者：
Newman, M. E. J.
我们为网络理论中一个长期存在的问题提供了解决方案，即创建一个合理的、可解决的网络模型，该模型显示集群性或传递性--网络节点的两个邻居也是邻居的倾向。彼此。我们展示了如何将标准随机图模型推广到聚类，并给出所产生的网络的各种属性的精确解，包括网络组件的大小，巨组件的大小，如果有一个，在巨组件形成的相变位置，以及在网络上渗流的相变位置。
We offer a solution to a long-standing problem in the theory of networks, the creation of a plausible, solvable model of a network that displays clustering or transitivity-the propensity for two neighbors of a network node also to be neighbors of one another. We show how standard random-graph models can be generalized to incorporate clustering and give exact solutions for various properties of the resulting networks, including sizes of network components, size of the giant component if there is one, position of the phase transition at which the giant component forms, and position of the phase transition for percolation on the network.