dc.rights.license | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.contributor.author | Serna, Ainhoa | |
dc.contributor.other | Gasparovic, Slaven | |
dc.date.accessioned | 2019-12-11T08:21:34Z | |
dc.date.available | 2019-12-11T08:21:34Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 2352-1457 | en |
dc.identifier.other | https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=153750 | en |
dc.identifier.uri | https://hdl.handle.net/20.500.11984/1516 | |
dc.description.abstract | The goal of the study of the paper is to propose a dashboard with dynamic graphics using a qualitatively and quantitatively approach to investigate the tourists’ satisfaction according by transport mode used. The methodology implemented in the research includes data collection from TripAdvisor.com with geographic locations and their integration with statistical territorial data. Text mining techniques are applied in order to assess tourists’ perceptions on success factors, which may be used as planning support tools. The case study concerns Croatia country and shows the value and complementarity of Social Media-related data with official statistics for transport and tourism planning. | en |
dc.description.sponsorship | Unión Europea | es |
dc.language.iso | eng | en |
dc.publisher | Elsevier Ltd. | en |
dc.rights | © 2018 The Authors | en |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Transport | en |
dc.subject | Social media | en |
dc.subject | Text mining | en |
dc.subject | Natural language processing | en |
dc.subject | User generated content | en |
dc.title | Transport analysis approach based on big data and text mining analysis from social media | en |
dcterms.accessRights | http://purl.org/coar/access_right/c_abf2 | en |
dcterms.source | Transportation Research Procedia | en |
local.description.peerreviewed | true | en |
local.description.publicationfirstpage | 291 | en |
local.description.publicationlastpage | 298 | en |
local.identifier.doi | http://dx.doi.org/10.1016/j.trpro.2018.10.105 | en |
local.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/681463/EU/COST at a turning point: A unique framework for pan-European ST cooperation as clear demonstration of European values/H2020 | en |
local.contributor.otherinstitution | https://ror.org/00mv6sv71 | es |
local.source.details | Vol. 33. Pp. 291-298. Elsevier, 2019 | eu_ES |
oaire.format.mimetype | application/pdf | |
oaire.file | $DSPACE\assetstore | |
oaire.resourceType | http://purl.org/coar/resource_type/c_6501 | en |
oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | en |