Towards a temporal network analysis of interactive WiFi users
Yan Zhang, Lin Wang, Yi-Qing Zhang, Xiang Li

TL;DR
This paper introduces a temporal network analysis of WiFi user interactions in a university, revealing how time-ordered contact data significantly differ from static models and impact understanding of human contact dynamics.
Contribution
It presents a novel temporal contact network constructed from WiFi logs, highlighting the importance of time order in human interaction analysis and potential superspreader identification.
Findings
Temporal contact networks differ from static aggregation in key features.
Time order influences the relationship between path length and duration.
Temporal analysis aids in identifying potential superspreaders.
Abstract
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…
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