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dc.contributor.authorHazarie, S
dc.contributor.authorBarbosa, H
dc.contributor.authorFrank, A
dc.contributor.authorMenezes, R
dc.contributor.authorGhoshal, G
dc.date.accessioned2021-01-04T12:13:32Z
dc.date.issued2020-07-22
dc.description.abstractThe recent availability of digital traces from information and communications technologies has facilitated the study of both individual- and population-level movement with unprecedented spatio-temporal resolution, enabling us to better understand a plethora of socio-economic processes such as urbanization, transportation, impact on the environment and epidemic spreading to name a few. Using empirical spatio-temporal trends, several mobility models have been proposed to explain the observed regularities in human movement. With the advent of the World Wide Web, a new type of virtual mobility has emerged that has begun to supplant many traditional facets of human activity. Here, we conduct a systematic analysis of physical and virtual movement, uncovering both similarities and differences in their statistical patterns. The differences manifest themselves primarily in the temporal regime, as a signature of the spatial and economic constraints inherent in physical movement, features that are predominantly absent in the virtual space. We demonstrate that once one moves to the time-independent space of events, i.e. the sequences of visited locations, these differences vanish, and the statistical patterns of physical and virtual mobility are identical. The observed similarity in navigating these markedly different domains points towards a common mechanism governing the movement patterns, a feature we describe through a Metropolis-Hastings type optimization model, where individuals navigate locations through decision-making processes resembling a cost-benefit analysis of the utility of locations. In contrast to existing phenomenological models of mobility, we show that our model can reproduce the commonalities in the empirically observed statistics with minimal input.en_GB
dc.description.sponsorshipUS Army Research Officeen_GB
dc.identifier.citationVol. 17 (168), article 20200250en_GB
dc.identifier.doi10.1098/rsif.2020.0250
dc.identifier.grantnumberW911NF-18-1-0421en_GB
dc.identifier.urihttp://hdl.handle.net/10871/124289
dc.language.isoenen_GB
dc.publisherRoyal Societyen_GB
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pubmed/32693745en_GB
dc.rights© 2020 The Author(s). Published by the Royal Society. All rights reserved.en_GB
dc.subjectmobilityen_GB
dc.subjectnetworksen_GB
dc.subjectoptimizationen_GB
dc.subjectscalingen_GB
dc.titleUncovering the differences and similarities between physical and virtual mobilityen_GB
dc.typeArticleen_GB
dc.date.available2021-01-04T12:13:32Z
exeter.place-of-publicationEnglanden_GB
dc.descriptionThis is the author accepted manuscript. The final version is available from the Royal Society via the DOI in this recorden_GB
dc.descriptionNote that the title of the author accepted manuscript is slightly different from that of the published versionen_GB
dc.descriptionData accessibility: All data used in this paper are open source. Web data are available at http://Webhistoryproject.blogspot.com, BrightKite data at https://snap.stanford.edu/data/loc-brightkite.html and Weeplaces at https://www.yongliu.org/datasets/.en_GB
dc.identifier.eissn1742-5662
dc.identifier.journalJournal of the Royal Society, Interfaceen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2020-06-30
exeter.funder::U. S. Army Research Officeen_GB
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2020-07-22
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2021-01-04T12:11:31Z
refterms.versionFCDAM
refterms.dateFOA2021-01-04T12:13:40Z
refterms.panelBen_GB


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