Structural transitions in scale-free networks.
Structural transitions in scale-free networks.
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DOI：
10.1103/physreve.67.056102
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发表时间：
2002-08
期刊：
影响因子：
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通讯作者：
G. Szabó;M. Alava;J. Kertész
中科院分区：
文献类型：
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作者：
G. Szabó;M. Alava;J. Kertész
真正成长的网络，例如万维网或基于个人连接的网络，除了小世界属性和缺乏特征规模之外，还具有高度集群的特征。对（Barabási-Albert）偏好依恋网络增长的适当修改可以捕获所有这些方面。我们提出了一种标度理论来描述广义模型的行为和聚类的平均场速率方程。这是针对特定情况求解的，对于 k 度节点的聚类，结果 C(k) 约为 1/k。该平均场指数与模拟一致，并且再现了许多真实网络的聚类。
Real growing networks such as the World Wide Web or personal connection based networks are characterized by a high degree of clustering, in addition to the small-world property and the absence of a characteristic scale. Appropriate modifications of the (Barabási-Albert) preferential attachment network growth capture all these aspects. We present a scaling theory to describe the behavior of the generalized models and the mean-field rate equation for clustering. This is solved for a specific case with the result C(k) approximately 1/k for the clustering of a node of degree k. This mean-field exponent agrees with simulations, and reproduces the clustering of many real networks.