Prediction limits of mobile phone activity modelling
Name
Kondor-2017-Prediction limits of mobile phone.pdf
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4.85 MB
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Author(s)
Kallus, Zsofia
Godor, Istavan
Kondor, Daniel
Grauwin, Sebastian
Sobolevsky, Stanislav
Ratti, Carlo
Date Issued
January 2017
Journal
Royal Society Open Science
Publisher
Royal Society
Citation
Kondor, Dániel; Grauwin, Sebastian; Kallus, Zsófia; Gódor, István; Sobolevsky, Stanislav and Ratti, Carlo. “Prediction Limits of Mobile Phone Activity Modelling.” Royal Society Open Science 4, no. 2 (February 2017): 160900 © 2017 The Authors
Version
Final published version
Abstract
Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also, we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events.
MIT Department
Massachusetts Institute of Technology. SENSEable City Laboratory
Terms of Use
Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1098/rsos.160900
