<?xml version='1.0' encoding='UTF-8'?><?xml-stylesheet href='static/style.xsl' type='text/xsl'?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-30T15:49:47Z</responseDate><request verb="GetRecord" identifier="oai:ebiltegia.mondragon.edu:20.500.11984/1516" metadataPrefix="rdf">https://ebiltegia.mondragon.edu/oai/request</request><GetRecord><record><header><identifier>oai:ebiltegia.mondragon.edu:20.500.11984/1516</identifier><datestamp>2024-03-04T11:13:13Z</datestamp><setSpec>com_20.500.11984_473</setSpec><setSpec>col_20.500.11984_478</setSpec></header><metadata><rdf:RDF xmlns:rdf="http://www.openarchives.org/OAI/2.0/rdf/" xmlns:ow="http://www.ontoweb.org/ontology/1#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:ds="http://dspace.org/ds/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/rdf/ http://www.openarchives.org/OAI/2.0/rdf.xsd">
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      <dc:title>Transport analysis approach based on big data and text mining analysis from social media</dc:title>
      <dc:creator>Serna, Ainhoa</dc:creator>
      <dc:contributor>Gasparovic, Slaven</dc:contributor>
      <dc:subject>Transport</dc:subject>
      <dc:subject>Social media</dc:subject>
      <dc:subject>Text mining</dc:subject>
      <dc:subject>Natural language processing</dc:subject>
      <dc:subject>User generated content</dc:subject>
      <dc:description>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.</dc:description>
      <dc:date>2019-12-11T08:21:34Z</dc:date>
      <dc:date>2019-12-11T08:21:34Z</dc:date>
      <dc:date>2018</dc:date>
      <dc:type>http://purl.org/coar/resource_type/c_6501</dc:type>
      <dc:identifier>2352-1457</dc:identifier>
      <dc:identifier>https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&amp;ficha_no=153750</dc:identifier>
      <dc:identifier>https://hdl.handle.net/20.500.11984/1516</dc:identifier>
      <dc:language>eng</dc:language>
      <dc:rights>Attribution-NonCommercial-NoDerivatives 4.0 International</dc:rights>
      <dc:rights>http://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
      <dc:rights>© 2018 The Authors</dc:rights>
      <dc:publisher>Elsevier Ltd.</dc:publisher>
   </ow:Publication>
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