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Detection of barriers to mobility in the smart city using Twitter

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dc.affiliation.dptoUC3M. Departamento de Ingeniería Telemáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Aplicaciones y Servicios Telemáticos (GAST)es
dc.affiliation.institutoUC3M. Instituto UC3M - Santander de Big Dataes
dc.contributor.authorSánchez Ávila, Mario
dc.contributor.authorMouriño García, Marcos Antonio
dc.contributor.authorArias Fisteus, Jesús
dc.contributor.authorSánchez Fernández, Luis
dc.contributor.funderMinisterio de Ciencia, Innovación y Universidades (España)es
dc.date.accessioned2021-05-18T11:51:48Z
dc.date.available2021-05-18T11:51:48Z
dc.date.issued2020-09-09
dc.description.abstractWe present a system that analyzes data extracted from the microbloging site Twitter to detect the occurrence of events and obstacles that can affect pedestrian mobility, with a special focus on people with impaired mobility. First, the system extracts tweets that match certain prede ned terms. Then, it obtains location information from them by using the location provided by Twitter when available, as well as searching the text of the tweet for locations. Finally, it applies natural language processing techniques to con rm that an actual event that affects mobility is reported and extract its properties (which urban element is affected and how). We also present some empirical results that validate the feasibility of our approach.en
dc.description.sponsorshipThis work was supported in part by the Analytics Using Sensor Data for FLATCity Project (Ministerio de Ciencia, innovación y Universidades/ERDF, EU) funded by the Spanish Agencia Estatal de Investigación (AEI), under Grant TIN2016-77158-C4-1-R, and in part by the European Regional Development Fund (ERDF).en
dc.format.extent10es
dc.identifier.bibliographicCitationIEEE Access, vol. 8, Sept. 2020, Pp. 168429-168438en
dc.identifier.doihttps://doi.org/10.1109/ACCESS.2020.3022834
dc.identifier.issn2169-3536
dc.identifier.publicationfirstpage168429es
dc.identifier.publicationlastpage168438es
dc.identifier.publicationtitleIEEE Accessen
dc.identifier.publicationvolume8es
dc.identifier.urihttps://hdl.handle.net/10016/32667
dc.identifier.uxxiAR/0000027508
dc.language.isoengen
dc.publisherIEEEen
dc.relation.projectIDGobierno de España. TIN2016-77158-C4-1-R/FLATCityen
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.en
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherMobility barrierrsen
dc.subject.otherSmartcityen
dc.subject.otherSocial sensingen
dc.subject.otherTransporten
dc.titleDetection of barriers to mobility in the smart city using Twitteren
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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