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Updated: May 9, 2026
16:14
Trajectory Data Analyses for Pedestrian Space-time Activity Study
Published on: February 25, 2013
Understanding metropolitan patterns of daily encounters
Lijun Sun1, Kay W Axhausen, Der-Horng Lee
1Future Cities Laboratory, Singapore-ETH Centre for Global Environmental Sustainability, Singapore 138602.
Summary
This study reveals reproducible temporal patterns in daily face-to-face encounters using public bus data. It uncovers a large, interconnected social network, explaining the "familiar strangers" phenomenon and its impact on social dynamics.
Area of Science:
- Social Network Analysis
- Urban Mobility Studies
- Human Behavior Dynamics
Background:
- Limited understanding of daily face-to-face encounter mechanisms.
- Lack of large-scale datasets on individual behaviors and collective interactions.
Purpose of the Study:
- To uncover encounter mechanisms and structures using travel smart card data.
- To construct a time-resolved in-vehicle social encounter network.
- To analyze individual and collective encounter patterns.
Main Methods:
- Utilized population-scale travel smart card data from public buses.
- Constructed a time-resolved in-vehicle social encounter network.
- Analyzed temporal patterns and individual encounter capabilities.
Main Results:
- Identified reproducible temporal patterns in physical encounters.
- Found collective regularities dominate individual encounter boundedness.
- Revealed a large, imperceptible small-world contact network of "co-presence" across the metropolitan area.
Conclusions:
- Individual encounter capability is rooted in daily behavioral regularity, explaining "familiar strangers."
- Repeated encounters form a large, interconnected network, not small communities.
- Understanding encounter patterns is crucial for social dynamics and diffusion processes.
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