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Approaching the limit of predictability in human mobility

Approaching the limit of predictability in human mobility
Approaching the limit of predictability in human mobility
In this study we analyze the travel patterns of 500,000 individuals in Cote d'Ivoire using mobile phone call data records. By measuring the uncertainties of movements using entropy, considering both the frequencies and temporal correlations of individual trajectories, we find that the theoretical maximum predictability is as high as 88%. To verify whether such a theoretical limit can be approached, we implement a series of Markov chain (MC) based models to predict the actual locations visited by each user. Results show that MC models can produce a prediction accuracy of 87% for stationary trajectories and 95% for non-stationary trajectories. Our findings indicate that human mobility is highly dependent on historical behaviors, and that the maximum predictability is not only a fundamental theoretical limit for potential predictive power, but also an approachable target for actual prediction accuracy.
Lu, Xin
a681bac0-d6d1-4e8e-a642-4ce42ae2cc9d
Wetter, Erik
dd9554f1-7107-4d5b-b19f-7198af551091
Bharti, Nita
2599876b-d215-44b4-ad2a-67460bbf7bdb
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Bengtsson, Linus
f7585eb4-9e78-422d-8178-4310985aa24e
Lu, Xin
a681bac0-d6d1-4e8e-a642-4ce42ae2cc9d
Wetter, Erik
dd9554f1-7107-4d5b-b19f-7198af551091
Bharti, Nita
2599876b-d215-44b4-ad2a-67460bbf7bdb
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Bengtsson, Linus
f7585eb4-9e78-422d-8178-4310985aa24e

Lu, Xin, Wetter, Erik, Bharti, Nita, Tatem, Andrew J. and Bengtsson, Linus (2013) Approaching the limit of predictability in human mobility. Scientific Reports, 3 (2923). (doi:10.1038/srep02923).

Record type: Article

Abstract

In this study we analyze the travel patterns of 500,000 individuals in Cote d'Ivoire using mobile phone call data records. By measuring the uncertainties of movements using entropy, considering both the frequencies and temporal correlations of individual trajectories, we find that the theoretical maximum predictability is as high as 88%. To verify whether such a theoretical limit can be approached, we implement a series of Markov chain (MC) based models to predict the actual locations visited by each user. Results show that MC models can produce a prediction accuracy of 87% for stationary trajectories and 95% for non-stationary trajectories. Our findings indicate that human mobility is highly dependent on historical behaviors, and that the maximum predictability is not only a fundamental theoretical limit for potential predictive power, but also an approachable target for actual prediction accuracy.

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More information

Published date: 11 October 2013
Organisations: Global Env Change & Earth Observation, WorldPop, Geography & Environment, PHEW – S (Spatial analysis and modelling), Population, Health & Wellbeing (PHeW)

Identifiers

Local EPrints ID: 358821
URI: https://eprints.soton.ac.uk/id/eprint/358821
PURE UUID: 85288409-394f-421c-8a38-8711f56abc36
ORCID for Andrew J. Tatem: ORCID iD orcid.org/0000-0002-7270-941X

Catalogue record

Date deposited: 14 Oct 2013 13:28
Last modified: 15 Aug 2019 00:36

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