# Two Categories of Indoor Interactive Dynamics of a Large-scale Human Population in a WiFi covered university campus

## TL;DR

This study analyzes large-scale indoor human interactions in a university campus using WiFi logs, revealing distinct interaction patterns, dynamics, and spatial behaviors with implications for understanding population contact networks.

## Contribution

It introduces a novel categorization of indoor interactions and characterizes their temporal and spatial dynamics using extensive WiFi data from a university campus.

## Key findings

- Interaction durations follow truncated power-law distributions.
- Transmission durations exhibit weekly periodicity.
- Individuals with burst interactions randomly select locations, while periodic interactors prefer specific spots.

## Abstract

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.