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Human dynamics in mobile social networks: A study of inter-node relationships

机译:移动社交网络中的人类动力学:节点间关系的研究

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To better understand human mobility patterns and interactions, it is important to go beyond the behavior of the individual level and mine the implicit correlation from the anonymized traces. We empirically studied some statistical properties of direct contact traces that recorded contacts between short range wireless communication devices. To describe internode relationships, we introduced a distance metric, i.e. Closeness Matrix. Closeness Matrix was inspired by the fact that, in social systems, technological systems, and biological systems, closely connected individuals tended to share common adjacent members. The results show that (1) mobility patterns of the individual level do not agree with that of population level since people have different personalities and behaviors; (2) closely connected individuals have similar power law exponents. Such understanding may promote more efficient behavior-aware protocols and applications.
机译:为了更好地了解人类的活动方式和相互作用,重要的是超越个人层面的行为并从匿名痕迹中挖掘隐式关联。我们从经验上研究了直接接触迹线的一些统计属性,这些迹线记录了短距离无线通信设备之间的接触。为了描述节点间的关系,我们引入了距离度量,即“接近度矩阵”。亲密度矩阵的灵感来自于这样一个事实,即在社会系统,技术系统和生物系统中,紧密联系的个人倾向于共享共同的相邻成员。结果表明:(1)由于人的性格和行为不同,个人水平的流动方式与人口水平的流动方式不一致。 (2)紧密联系的个人具有相似的幂律指数。这种理解可以促进更有效的行为感知协议和应用程序。

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