  To explore large-scale population indoor interactions, we analyze 18,715
users' WiFi access logs recorded in a Chinese university campus during 3
months, and define two categories of human interactions, the event interaction
(EI) and the temporal interaction (TI). The EI helps construct a transmission
graph, and the TI helps build an interval graph. The dynamics of EIs show that
their active durations are truncated power-law distributed, which is
independent on the number of involved individuals. The transmission duration
presents a truncated power-law behavior at the daily timescale with weekly
periodicity. Besides, those `leaf' individuals in the aggregated contact
network may participate in the `super-connecting cliques' in the aggregated
transmission graph. Analyzing the dynamics of the interval graph, we find that
the probability distribution of TIs' inter-event duration also displays a
truncated power-law pattern at the daily timescale with weekly periodicity,
while the pairwise individuals with burst interactions are prone to randomly
select their interactive locations, and those individuals with periodic
interactions have preferred interactive locations.
