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Limits of Predictability in Human Mobility
Abstract
Predictable Travel Routines: While people rarely perceive their actions to be random, current models of human activity are fundamentally stochastic. Processes that rely on human mobility patterns, like the prediction of new epidemics, traffic engineering, or city planning, could benefit from highly accurate predictive models. To investigate the predictability of human dynamics, Song et al. (p. 1018 ) used the recorded trajectories of millions of mobile phone users, collected by mobile phone companies and anonymized for research purposes. They hypothesized that given the wide range of travel patterns that different users follow, there would be significant differences between their predictability as well: Users who travel less should be easier to predict than those who are constantly on the road. Surprisingly, there was 93% predictability across the whole user base, and individuals' predictability did not in general fall significantly below 80%.
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“Still, human mobility is known to follow certain universal principles, such as scaling laws of mobility (Alessandretti et al. 2020;Pappalardo et al. 2016;Song et al. 2010b), which suggests that our findings may reflect more general behavioral regularities.”
From Visitation patterns across mobility groups: wandering, commuting, and exploring (2026) · cites this paper as Song et al. 2010b
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Flagged first, then by citations
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“B] have been used in the past for research purposes 4–18 and to provide personalized services to users 19 .”
BackgroundInfluentialA universal model for mobility and migration patterns
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Self-citation
Metadata
- Authors
- Song, C., Qu, Z., Blumm, N., & Barabási, A.-L.
- Affiliations
- Northeastern University (US)
- Center for Complex Network Research, Departments of Physics, Biology, and Computer Science, Northeastern University, Boston, MA 02115, USA.
- ORCID
- Song, Chaoming
- Venue
- Science
- Published
- 2010-02-19
- Volume
- 327
- Issue
- 5968
- Pages
- 1018-1021
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W1987228002
- Cited by
- 3,234
- References
- 25
- Citations by year
- 2026: 125 · 2025: 113 · 2024: 149 · 2023: 133 · 2022: 206 · 2021: 222 · 2020: 221 · 2019: 274 · 2018: 294 · 2017: 249 · 2016: 258 · 2015: 264 · 2014: 225 · 2013: 203 · 2012: 140
- FWCI
- 390.44
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Complex Systems and Time Series Analysis
- Physical Sciences › Computer Science › Computer Networks and Communications › Opportunistic and Delay-Tolerant Networks
- Keywords
- human mobility, predictability, individual mobility patterns, epidemic forecasting, traffic engineering, urban planning
- MeSH terms
- Behavior, Forecasting, Humans, Human Activities, Locomotion, Probability, Travel, Models, Statistical, Cell Phone
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