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• W1963905090 abstract "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. The availability of pervasive data has opened up possibilities for quantitative approaches to many phenomena, but extracting useful information from huge datasets is difficult. Here, Louail et al. propose a method to extract a coarse-grained signature of large weighted networks and apply it to mobility networks." @default.
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• W1963905090 date "2015-01-21" @default.
• W1963905090 modified "2023-10-13" @default.
• W1963905090 title "Uncovering the spatial structure of mobility networks" @default.
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• W1963905090 doi "https://doi.org/10.1038/ncomms7007" @default.
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