  Extensive efforts have been devoted to characterizing the rich connectivity
patterns among the nodes (components) of such complex networks (systems), and
in the course of development of research in this area, people have been
prompted to address on a fundamental question: How does the fascinating yet
complex topological features of a network affect or determine the collective
behavior and performance of the networked system? While elegant attempts to
address this core issue have been made, for example, from the viewpoints of
synchronization, epidemics, evolutionary cooperation, and the control of
complex networks, theoretically or empirically, this widely concerned key
question still remains open in the newly emergent field of network science.
Such fruitful advances also push the desire to understand (mobile) social
networks and characterize human social populations with the interdependent
collective dynamics as well as the behavioral patterns. Nowadays, a great deal
of digital technologies are unobtrusively embedded into the physical world of
human daily activities, which offer unparalleled opportunities to explosively
digitize human physical interactions, who is contacting with whom at what time.
Such powerful technologies include the Bluetooth, the active Radio Frequency
Identification (RFID) technology, wireless sensors and, more close to our
interest in this paper, the WiFi technology. As a snapshot of the modern
society, a university is in the coverage of WiFi signals, where the WiFi system
records the digital access logs of the authorized WiFi users when they access
the campus wireless services. Such WiFi access records, as the indirect proxy
data, work as the effective proxy of a large-scale population's social
interactions.
