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dc.contributor.authorLouail, Thomas-
dc.contributor.authorLenormand, Maxime-
dc.contributor.authorPicornell, Miguel-
dc.contributor.authorCantu Ros, O. G.-
dc.contributor.authorHerranz, Ricardo-
dc.contributor.authorFrías-Martínez, Enrique-
dc.contributor.authorRamasco, José J.-
dc.contributor.authorBarthelemy, Marc-
dc.date.accessioned2016-06-15T08:43:32Z-
dc.date.available2016-06-15T08:43:32Z-
dc.date.issued2015-01-21-
dc.identifierissn: 2041-1723-
dc.identifier.citationNature Communications 6: 6007 (2015)-
dc.identifier.urihttp://hdl.handle.net/10261/133481-
dc.description.abstract© 2015 Macmillan Publishers Limited. All rights reserved. The extraction of a clear and simple footprint of the structure of large, weighted and directed networks is a general problem that has relevance for many applications. An important example is seen in origin-destination matrices, which contain the complete information on commuting flows, but are difficult to analyze and compare. We propose here a versatile method, which extracts a coarse-grained signature of mobility networks, under the form of a 2 × 2 matrix that separates the flows into four categories. We apply this method to origin-destination matrices extracted from mobile phone data recorded in 31 Spanish cities. We show that these cities essentially differ by their proportion of two types of flows: integrated (between residential and employment hotspots) and random flows, whose importance increases with city size. Finally, the method allows the determination of categories of networks, and in the mobility case, the classification of cities according to their commuting structure.-
dc.description.sponsorshipThe research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement 318367 (EUNOIA project). M.L. and J.J.R. received partial financial support from the Spanish Ministry of Economy (MINECO) and FEDER (EU) under projects MODASS (FIS2011-24785) and INTENSE@COSYP (FIS2012-30634). The work of M.L. has been funded under the PD/004/2013 project, from the Conselleria de Educacion, Cultura y Universidades of the Government of the Balearic Islands and from the European Social Fund through the Balearic Islands ESF operational program for 2013–2017.-
dc.publisherNature Publishing Group-
dc.relationinfo:eu-repo/grantAgreement/EC/FP7/318367-
dc.relation.isversionofPublisher's version-
dc.rightsopenAccess-
dc.titleUncovering the spatial structure of mobility networks-
dc.typeartículo-
dc.identifier.doi10.1038/ncomms7007-
dc.relation.publisherversionhttp://dx.doi.org/10.1038/ncomms7007-
dc.date.updated2016-06-15T08:43:33Z-
dc.description.versionPeer Reviewed-
dc.language.rfc3066eng-
dc.contributor.funderEuropean Commission-
dc.contributor.funderMinisterio de Economía y Competitividad (España)-
dc.contributor.funderGovern de les Illes Balears-
dc.relation.csic-
dc.identifier.funderhttp://dx.doi.org/10.13039/501100000780es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100003329es_ES
dc.type.coarhttp://purl.org/coar/resource_type/c_6501es_ES
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.openairetypeartículo-
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