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dc.contributor.authorLenormand, Maximees_ES
dc.contributor.authorLouail, Thomases_ES
dc.contributor.authorBarthelemy, Marces_ES
dc.contributor.authorRamasco, José J.es_ES
dc.date.accessioned2017-11-24T11:08:07Z-
dc.date.available2017-11-24T11:08:07Z-
dc.date.issued2016-
dc.identifier.citationProceedings of the 2016 Spatial Accuracy Conference: 9-17 (2016)es_ES
dc.identifier.urihttp://hdl.handle.net/10261/157704-
dc.descriptionExtended version of the conference paper published in the proceedings of the 2016 Spatial Accuracy Conference, p 9-17, Montpellier, France.es_ES
dc.description.abstractAn increasing number of human activities are studied using data produced by individuals' ICT devices. In particular, when ICT data contain spatial information, they represent an invaluable source for analyzing urban dynamics. However, there have been relatively few contributions investigating the robustness of this type of results against fluctuations of data characteristics. Here, we present a stability analysis of higher-level information extracted from mobile phone data passively produced during an entire year by 9 million individuals in Senegal. We focus on two information-retrieval tasks: (a) the identification of land use in the region of Dakar from the temporal rhythms of the communication activity; (b) the identification of home and work locations of anonymized individuals, which enable to construct Origin-Destination (OD) matrices of commuting flows. Our analysis reveal that the uncertainty of results highly depends on the sample size, the scale and the period of the year at which the data were gathered. Nevertheless, the spatial distributions of land use computed for different samples are remarkably robust: on average, we observe more than 75% of shared surface area between the different spatial partitions when considering activity of at least 100,000 users whatever the scale. The OD matrix is less stable and depends on the scale with a share of at least 75% of commuters in common when considering all types of flows constructed from the home-work locations of 100,000 users. For both tasks, better results can be obtained at larger levels of aggregation or by considering more users. These results confirm that ICT data are very useful sources for the spatial analysis of urban systems, but that their reliability should in general be tested more thoroughly.es_ES
dc.language.isoenges_ES
dc.relation.isversionofPreprintes_ES
dc.rightsopenAccesses_ES
dc.titleIs spatial information in ICT data reliable?es_ES
dc.typecomunicación de congresoes_ES
dc.description.peerreviewedNoes_ES
dc.relation.csices_ES
oprm.item.hasRevisionno ko 0 false*
dc.type.coarhttp://purl.org/coar/resource_type/c_5794es_ES
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypecomunicación de congreso-
item.cerifentitytypePublications-
item.grantfulltextopen-
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