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Multi-scale spatio-temporal analysis of human mobility

The recent availability of digital traces generated by phone calls and online logins has significantly increased the scientific understanding of human mobility. Until now, however, limited data resolution and coverage have hindered a coherent description of human displacements across different spati...

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Autores principales: Alessandretti, Laura, Sapiezynski, Piotr, Lehmann, Sune, Baronchelli, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5310761/
https://www.ncbi.nlm.nih.gov/pubmed/28199347
http://dx.doi.org/10.1371/journal.pone.0171686
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author Alessandretti, Laura
Sapiezynski, Piotr
Lehmann, Sune
Baronchelli, Andrea
author_facet Alessandretti, Laura
Sapiezynski, Piotr
Lehmann, Sune
Baronchelli, Andrea
author_sort Alessandretti, Laura
collection PubMed
description The recent availability of digital traces generated by phone calls and online logins has significantly increased the scientific understanding of human mobility. Until now, however, limited data resolution and coverage have hindered a coherent description of human displacements across different spatial and temporal scales. Here, we characterise mobility behaviour across several orders of magnitude by analysing ∼850 individuals’ digital traces sampled every ∼16 seconds for 25 months with ∼10 meters spatial resolution. We show that the distributions of distances and waiting times between consecutive locations are best described by log-normal and gamma distributions, respectively, and that natural time-scales emerge from the regularity of human mobility. We point out that log-normal distributions also characterise the patterns of discovery of new places, implying that they are not a simple consequence of the routine of modern life.
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spelling pubmed-53107612017-03-03 Multi-scale spatio-temporal analysis of human mobility Alessandretti, Laura Sapiezynski, Piotr Lehmann, Sune Baronchelli, Andrea PLoS One Research Article The recent availability of digital traces generated by phone calls and online logins has significantly increased the scientific understanding of human mobility. Until now, however, limited data resolution and coverage have hindered a coherent description of human displacements across different spatial and temporal scales. Here, we characterise mobility behaviour across several orders of magnitude by analysing ∼850 individuals’ digital traces sampled every ∼16 seconds for 25 months with ∼10 meters spatial resolution. We show that the distributions of distances and waiting times between consecutive locations are best described by log-normal and gamma distributions, respectively, and that natural time-scales emerge from the regularity of human mobility. We point out that log-normal distributions also characterise the patterns of discovery of new places, implying that they are not a simple consequence of the routine of modern life. Public Library of Science 2017-02-15 /pmc/articles/PMC5310761/ /pubmed/28199347 http://dx.doi.org/10.1371/journal.pone.0171686 Text en © 2017 Alessandretti et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Alessandretti, Laura
Sapiezynski, Piotr
Lehmann, Sune
Baronchelli, Andrea
Multi-scale spatio-temporal analysis of human mobility
title Multi-scale spatio-temporal analysis of human mobility
title_full Multi-scale spatio-temporal analysis of human mobility
title_fullStr Multi-scale spatio-temporal analysis of human mobility
title_full_unstemmed Multi-scale spatio-temporal analysis of human mobility
title_short Multi-scale spatio-temporal analysis of human mobility
title_sort multi-scale spatio-temporal analysis of human mobility
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5310761/
https://www.ncbi.nlm.nih.gov/pubmed/28199347
http://dx.doi.org/10.1371/journal.pone.0171686
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