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Uncovering the spatial structure of mobility networks

Abstract : The extraction of a clear and simple footprint of the structure of large, weighted and directed networks is a general problem that has many applications. An important example is given by 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 thirty-one 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 to determine categories of networks, and in the mobility case to classify cities according to their commuting structure. The increasing availability of pervasive data in various fields has opened exciting possibilities of renewed quanti-tative approaches to many phenomena. This is particu-larly true for cities and urban systems for which different devices at different scales produce a very large amount of data potentially useful to construct a 'new science of cities' [1].
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Submitted on : Friday, February 20, 2015 - 2:27:39 PM
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Thomas Louail, Maxime Lenormand, Miguel Picornell, García Oliva, Ricardo Herranz, et al.. Uncovering the spatial structure of mobility networks. Nature Communications, Nature Publishing Group, 2015, 6, pp.6007. ⟨10.1038/ncomms7007⟩. ⟨cea-01118965⟩

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