Tracking urban human activity from mobile phone calling patterns

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorMonsivais, Danielen_US
dc.contributor.authorGhosh, Asimen_US
dc.contributor.authorBhattacharya, Kunalen_US
dc.contributor.authorDunbar, Robin I.M.en_US
dc.contributor.authorKaski, Kimmoen_US
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.groupauthorKaski Kimmo groupen
dc.date.accessioned2018-02-09T09:56:58Z
dc.date.available2018-02-09T09:56:58Z
dc.date.issued2017-11-01en_US
dc.description.abstractTimings of human activities are marked by circadian clocks which in turn are entrained to different environmental signals. In an urban environment the presence of artificial lighting and various social cues tend to disrupt the natural entrainment with the sunlight. However, it is not completely understood to what extent this is the case. Here we exploit the large-scale data analysis techniques to study the mobile phone calling activity of people in large cities to infer the dynamics of urban daily rhythms. From the calling patterns of about 1,000,000 users spread over different cities but lying inside the same time-zone, we show that the onset and termination of the calling activity synchronizes with the east-west progression of the sun. We also find that the onset and termination of the calling activity of users follows a yearly dynamics, varying across seasons, and that its timings are entrained to solar midnight. Furthermore, we show that the average mid-sleep time of people living in urban areas depends on the age and gender of each cohort as a result of biological and social factors.en
dc.description.versionPeer revieweden
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationMonsivais, D, Ghosh, A, Bhattacharya, K, Dunbar, R I M & Kaski, K 2017, 'Tracking urban human activity from mobile phone calling patterns', PLoS Computational Biology, vol. 13, no. 11, e1005824, pp. 1-16. https://doi.org/10.1371/journal.pcbi.1005824en
dc.identifier.doi10.1371/journal.pcbi.1005824en_US
dc.identifier.issn1553-734X
dc.identifier.issn1553-7358
dc.identifier.otherPURE UUID: 43928848-774f-4096-a498-fd55bff00f94en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/43928848-774f-4096-a498-fd55bff00f94en_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/16609382/journal.pcbi.1005824.pdf
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/29810
dc.identifier.urnURN:NBN:fi:aalto-201802091306
dc.language.isoenen
dc.publisherPublic Library of Science
dc.relation.ispartofseriesPLoS Computational Biologyen
dc.relation.ispartofseriesVolume 13, issue 11, pp. 1-16en
dc.rightsopenAccessen
dc.titleTracking urban human activity from mobile phone calling patternsen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion

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