Unravelling daily human mobility motifs
Massachusetts Institute of Technology · Max Planck Institute for Dynamics and Self-Organization · +2 more institutions
Abstract
Human mobility is differentiated by time scales. While the mechanism for long time scales has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we uncover the mechanism responsible for the daily mobility patterns by analysing the temporal and spatial trajectories of thousands of persons as individual networks. Using the concept of motifs from network theory, we find only 17 unique networks are present in daily mobility and they follow simple rules. These networks, called here motifs, are sufficient to capture up to 90 per cent of the population in surveys and mobile phone datasets for different countries. Each individual exhibits a characteristic motif, which seems to be…
Citation impact
- FWCI
- 74.54
- Percentile
- 100%
- References
- 47
Authors
5- CSChristian SchneiderCorresponding
Massachusetts Institute of Technology
- VBVitaly Belik
Max Planck Institute for Dynamics and Self-Organization, Massachusetts Institute of Technology
- TCThomas Couronné
Orange (France)
- ZSZbigniew Smoreda
Orange (France)
- MCMarta C. González
Engineering Systems (United States), Massachusetts Institute of Technology
Topics & keywords
- Computer science
- Markov chain
- Human dynamics
- Mechanism (biology)
- Complex network
- TRIPS architecture
- Artificial intelligence
- Machine learning