An Energy-Based Model for Spatial Social Networks
An Energy-Based Model for Spatial Social Networks
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基于能量的空间社交网络模型
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
M. Tomassini
中科院分区：
文献类型：
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作者：
A. Antonioni;Mattia Egloff;M. Tomassini
在过去的十年中，由于丰富的数据和充足的软件工具，复杂网络在许多学科中得到了深入的研究。这项工作的大部分涉及网络，其中距离没有物理意义，只是以边缘跳数衡量的无量纲量。然而，在许多情况下，网络嵌入的物理空间和节点之间的实际距离很重要，例如在地理和交通网络中。随机几何图 (RGG) 是一种标准空间网络模型，它在空间网络中的作用类似于 Erd´´ 随机图在关系网络中的作用。在这项工作中，我们提出了 RGG 构造的扩展，以定义一个新模型来构建基于能量作为创建链接的现实约束的二维空间网络。构建的网络与实际社交网络具有一些共同的属性。
In the past decade, thanks to abundant data and adequate software tools, complex networks have been thoroughly investigated in many disciplines. Most of this work has dealt with networks in which distances do not have physical meaning and are just dimensionless quantities measured in terms of edge hops. However, in many cases the physical space in which networks are embedded and the actual distances between nodes are important, such as in geographical and transportation networks. The Random Geometric Graph (RGG) is a standard spatial network model that plays a role for spatial networks similar to the one played by the Erd¨´ random graph for relational ones. In this work we present an extension of the RGG construction to define a new model to build bi-dimensional spatial networks based on energy as realistic constraint to create the links. The constructed networks have several properties in common with those of actual social networks.