Detection of barriers to mobility in the smart city using Twitter

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Show simple item record Sánchez Ávila, Mario Mouriño García, Marcos Antonio Arias Fisteus, Jesús Sánchez Fernández, Luis 2021-05-18T11:51:48Z 2021-05-18T11:51:48Z 2020-09-09
dc.identifier.bibliographicCitation IEEE Access, vol. 8, Sept. 2020, Pp. 168429-168438
dc.identifier.issn 2169-3536
dc.description.abstract We 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.
dc.description.sponsorship This 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).
dc.format.extent 10
dc.language.iso eng
dc.publisher IEEE
dc.rights This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.subject.other Mobility barrierrs
dc.subject.other Smartcity
dc.subject.other Social sensing
dc.subject.other Transport
dc.title Detection of barriers to mobility in the smart city using Twitter
dc.type article
dc.subject.eciencia Telecomunicaciones
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. TIN2016-77158-C4-1-R/FLATCity
dc.type.version publishedVersion
dc.identifier.publicationfirstpage 168429
dc.identifier.publicationlastpage 168438
dc.identifier.publicationtitle IEEE Access
dc.identifier.publicationvolume 8
dc.identifier.uxxi AR/0000027508
dc.contributor.funder Ministerio de Ciencia, Innovación y Universidades (España)
dc.affiliation.dpto UC3M. Departamento de Ingeniería Telemática
dc.affiliation.instituto UC3M. Instituto UC3M - Santander de Big Data
dc.affiliation.grupoinv UC3M. Grupo de Investigación: Aplicaciones y Servicios Telemáticos (GAST)
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