Spatially Distributed Social Complex Networks
Spatially Distributed Social Complex Networks
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DOI：
10.1103/physrevx.4.011008
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发表时间：
2014-01-28
影响因子：
12.5
通讯作者：
ben-Avraham, Daniel
中科院分区：
文献类型：
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作者：
Frasco, Gerald F.;Sun, Jie;ben-Avraham, Daniel
我们提出了一个简单的随机模型，既考虑到一个国家内的人的地理分布和他们的复杂网络的连接。该模型的设计目的是建立一个无标度的社会联系网络，在视觉上类似于地球夜间卫星图片中的地理分布，并根据人口规模（但对于最大的城市）对城市进行排名，并反映出高度联系的个人往往生活在人口稠密的地区的概念。它还产生了一些关于城市增长率（按人口规模）的Gibrat定律的有趣见解，部分支持最近对真实的数据的分析结果[Rozenfeld等人，Proc. Natl. Acad. Sci. U.S.A.105，18702（2008）.]。该模型在城市人口和城市人口密度之间产生了非平凡的关系，在社会连通性和城市人口之间产生了超线性关系，这两种关系似乎都与真实的数据非常一致。
We propose a bare-bones stochastic model that takes into account both the geographical distribution of people within a country and their complex network of connections. The model, which is designed to give rise to a scale-free network of social connections and to visually resemble the geographical spread seen in satellite pictures of the Earth at night, gives rise to a power-law distribution for the ranking of cities by population size (but for the largest cities) and reflects the notion that highly connected individuals tend to live in highly populated areas. It also yields some interesting insights regarding Gibrat's law for the rates of city growth (by population size), in partial support of the findings in a recent analysis of real data [Rozenfeld et al., Proc. Natl. Acad. Sci. U.S.A. 105, 18702 (2008).]. The model produces a nontrivial relation between city population and city population density and a superlinear relationship between social connectivity and city population, both of which seem quite in line with real data.