2024-03-29T00:33:15Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1334812018-09-13T08:59:11Zcom_10261_2855com_10261_4col_10261_2857
Uncovering the spatial structure of mobility networks
Louail, Thomas
Lenormand, Maxime
Picornell, Miguel
Cantu Ros, O. G.
Herranz, Ricardo
Frías-Martínez, Enrique
Ramasco, José J.
Barthelemy, Marc
European Commission
Ministerio de Economía y Competitividad (España)
Govern de les Illes Balears
© 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.
2016-06-15T08:43:32Z
2016-06-15T08:43:32Z
2015-01-21
2016-06-15T08:43:33Z
artículo
Nature Communications 6: 6007 (2015)
http://hdl.handle.net/10261/133481
10.1038/ncomms7007
http://dx.doi.org/10.13039/501100000780
http://dx.doi.org/10.13039/501100003329
eng
Publisher's version
http://dx.doi.org/10.1038/ncomms7007
Sí
info:eu-repo/grantAgreement/EC/FP7/318367
openAccess
Nature Publishing Group