In this paper we devise a generative random network model with core-periphery properties whose core nodes act as sublinear dominators, that is, if the network has $n$ nodes, the core has size $o(n)$ and dominates the entire network. We show that instances generated by this model exhibit power law degree distributions, and incorporates small-world phenomena. We also fit our model in a variety of real-world networks.

中文翻译：

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亚线性控制和核心外围网络

在本文中，我们设计了一个具有核心外围属性的生成随机网络模型，其核心节点充当次线性支配者，也就是说，如果网络具有$ n $个节点，则核心的大小为$ o（n）$，并且支配整个网络。我们证明了该模型生成的实例展示了幂律度分布，并包含了小世界现象。我们也将模型拟合到各种现实网络中。