Understanding predictability and exploration in human mobility
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13688_2017_Article_129.pdf
Size
1.98 MB
Format
Adobe PDF
Checksum (MD5)
b71a01874a92a8e9bda9129880065a7a
Author(s)
Lehmann, Sune
Cuttone, Andrea
Gonzalez, Marta C.
Date Issued
January 2018
Journal
EPJ Data Science
Publisher
Springer
Citation
Cuttone, Andrea et al. "Understanding predictability and exploration in human mobility." EPJ Data Science 2018, 7 (January 2018): 2 © 2018 The Author(s)
Version
Final published version
Abstract
Predictive models for human mobility have important applications in many fields including traffic control, ubiquitous computing, and contextual advertisement. The predictive performance of models in literature varies quite broadly, from over 90% to under 40%. In this work we study which underlying factors - in terms of modeling approaches and spatio-temporal characteristics of the data sources - have resulted in this remarkably broad span of performance reported in the literature. Specifically we investigate which factors influence the accuracy of next-place prediction, using a high-precision location dataset of more than 400 users observed for periods between 3 months and one year. We show that it is much easier to achieve high accuracy when predicting the time-bin location than when predicting the next place. Moreover, we demonstrate how the temporal and spatial resolution of the data have strong influence on the accuracy of prediction. Finally we reveal that the exploration of new locations is an important factor in human mobility, and we measure that on average 20-25% of transitions are to new places, and approx. 70% of locations are visited only once. We discuss how these mechanisms are important factors limiting our ability to predict human mobility. Keywords: human mobility; next-location prediction; predictability
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1140/epjds/s13688-017-0129-1
