走向交互式WiFi用户的时态网络分析

Yan Zhang, Lin Wang, Yi-Qing Zhang, Xiang Li
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引用次数: 63

摘要

复杂网络用于描述复杂系统的拓扑特征。网络的结构表征了系统各元素之间的相互作用,有助于研究发生在网络上的许多动态过程。在以往的研究中,动态系统的拓扑基础结构被简化为静态不变的骨架。然而,这一假设不能涵盖许多时间进化网络的时间特征,这些网络的组成部分是不断进化和突变的。在这封信中,我们利用中国某大学校园WiFi用户的日志数据,将时间维度注入到动态人际接触网络的构建中。通过与传统聚合方法的定量比较,我们发现时间接触网络在可达性、路径长度分布等诸多特征上存在差异。时间路径长度与持续时间的相关性不仅取决于它们的定义,还受到一定社会环境下人类活动的微观动力特征的影响。本文研究的个体互动事件的时间顺序在理解人类近距离互动的许多动态过程中起着关键作用。此外,我们的研究还提供了一种有希望的方法,通过区分充当中继枢纽的节点来识别潜在的超级传播者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a temporal network analysis of interactive WiFi users
Complex networks are used to depict topological features of complex systems. The structure of a network characterizes the interactions among elements of the system, and facilitates the study of many dynamical processes taking place on it. In previous investigations, the topological infrastructure underlying dynamical systems is simplified as a static and invariable skeleton. However, this assumption cannot cover the temporal features of many time-evolution networks, whose components are evolving and mutating. In this letter, utilizing the log data of WiFi users in a Chinese university campus, we infuse the temporal dimension into the construction of dynamical human contact network. By quantitative comparison with the traditional aggregation approach, we find that the temporal contact network differs in many features, e.g., the reachability, the path length distribution. We conclude that the correlation between temporal path length and duration is not only determined by their definitions, but also influenced by the micro-dynamical features of human activities under certain social circumstance as well. The time order of individuals' interaction events plays a critical role in understanding many dynamical processes via human close proximity interactions studied in this letter. Besides, our study also provides a promising measure to identify the potential superspreaders by distinguishing the nodes functioning as the relay hub.
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