Destination image analytics through traveller-generated content

The explosion of content generated by users, in parallel with the spectacular growth of social media and the proliferation of mobile devices, is causing a paradigm shift in research. Surveys or interviews are no longer necessary to obtain users' opinions, because researchers can get this inform...

Full description

Bibliographic Details
Author: Mariné Roig, Estela
Format: article
Status:Published version
Publication Date:2019
Country:España
Institution:Universitat de Lleida (UdL)
Repository:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/66493
Online Access:https://doi.org/10.3390/su11123392
http://hdl.handle.net/10459.1/66493
Access Level:Open access
Keyword:Destination image
User-generated content
Big data analytics
Online travel review
Sentiment analysis
id ES_3cc0fb8737c3d455d94247d13bfcbd2c
oai_identifier_str oai:repositori.udl.cat:10459.1/66493
network_acronym_str ES
network_name_str España
repository_id_str
spelling Destination image analytics through traveller-generated contentMariné Roig, EstelaDestination imageUser-generated contentBig data analyticsOnline travel reviewSentiment analysisThe explosion of content generated by users, in parallel with the spectacular growth of social media and the proliferation of mobile devices, is causing a paradigm shift in research. Surveys or interviews are no longer necessary to obtain users' opinions, because researchers can get this information freely on social media. In the field of tourism, online travel reviews (OTRs) hosted on travel-related websites stand out. The objective of this article is to demonstrate the usefulness of OTRs to analyse the image of a tourist destination. For this, a theoretical and methodological framework is defined, as well as metrics that allow for measuring different aspects (designative, appraisive and prescriptive) of the tourist image. The model is applied to the region of Attica (Greece) through a random sample of 300,000 TripAdvisor OTRs about attractions, activities, restaurants and hotels written in English between 2013 and 2018. The results show trends, preferences, assessments, and opinions from the demand side, which can be useful for destination managers in optimising the distribution of available resources and promoting sustainability.MDPI2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.3390/su11123392http://hdl.handle.net/10459.1/66493reponame:Repositori Obert UdL instname:Universitat de Lleida (UdL)InglésReproducció del document publicat a https://doi.org/10.3390/su11123392Sustainability, 2019, vol. 11, núm. 12, p. 1-23cc-by (c) Mariné Roig, Estela, 2019info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/oai:repositori.udl.cat:10459.1/664932026-06-24T12:42:17Z
dc.title.none.fl_str_mv Destination image analytics through traveller-generated content
title Destination image analytics through traveller-generated content
spellingShingle Destination image analytics through traveller-generated content
Mariné Roig, Estela
Destination image
User-generated content
Big data analytics
Online travel review
Sentiment analysis
title_short Destination image analytics through traveller-generated content
title_full Destination image analytics through traveller-generated content
title_fullStr Destination image analytics through traveller-generated content
title_full_unstemmed Destination image analytics through traveller-generated content
title_sort Destination image analytics through traveller-generated content
dc.creator.none.fl_str_mv Mariné Roig, Estela
author Mariné Roig, Estela
author_facet Mariné Roig, Estela
author_role author
dc.subject.none.fl_str_mv Destination image
User-generated content
Big data analytics
Online travel review
Sentiment analysis
topic Destination image
User-generated content
Big data analytics
Online travel review
Sentiment analysis
description The explosion of content generated by users, in parallel with the spectacular growth of social media and the proliferation of mobile devices, is causing a paradigm shift in research. Surveys or interviews are no longer necessary to obtain users' opinions, because researchers can get this information freely on social media. In the field of tourism, online travel reviews (OTRs) hosted on travel-related websites stand out. The objective of this article is to demonstrate the usefulness of OTRs to analyse the image of a tourist destination. For this, a theoretical and methodological framework is defined, as well as metrics that allow for measuring different aspects (designative, appraisive and prescriptive) of the tourist image. The model is applied to the region of Attica (Greece) through a random sample of 300,000 TripAdvisor OTRs about attractions, activities, restaurants and hotels written in English between 2013 and 2018. The results show trends, preferences, assessments, and opinions from the demand side, which can be useful for destination managers in optimising the distribution of available resources and promoting sustainability.
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.3390/su11123392
http://hdl.handle.net/10459.1/66493
url https://doi.org/10.3390/su11123392
http://hdl.handle.net/10459.1/66493
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a https://doi.org/10.3390/su11123392
Sustainability, 2019, vol. 11, núm. 12, p. 1-23
dc.rights.none.fl_str_mv cc-by (c) Mariné Roig, Estela, 2019
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv cc-by (c) Mariné Roig, Estela, 2019
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Repositori Obert UdL
instname:Universitat de Lleida (UdL)
instname_str Universitat de Lleida (UdL)
reponame_str Repositori Obert UdL
collection Repositori Obert UdL
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869406396107194368
score 15.81155

Similar Items