Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/25466Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Silva, B. | - |
| dc.contributor.author | Moro, S. | - |
| dc.contributor.author | Marques, C. | - |
| dc.contributor.editor | Reis, J. L., Parra López, E., Moutinho, L., and Santos, J. P. M. dos. | - |
| dc.date.accessioned | 2022-05-19T14:31:07Z | - |
| dc.date.available | 2022-05-19T14:31:07Z | - |
| dc.date.issued | 2022 | - |
| dc.identifier.isbn | 978-981-16-9268-0 | - |
| dc.identifier.issn | 2190-3018 | - |
| dc.identifier.uri | http://hdl.handle.net/10071/25466 | - |
| dc.description.abstract | This study aims to understand how the COVID-19 pandemic affected the hotel sector and to identify the current traveler demands. The traveler’s re-views were analyzed based on sentiment analysis and a guest satisfaction model was also proposed, demonstrating a data mining approach within tourism and hospitality research. Given its popularity, TripAdvisor was the chosen platform for collection of hotel reviews in London and Paris. Text data were extracted from reviews made in two time periods, before and during the COVID-19 pan-demic. The sentiment and specific aspects highlighted by travelers were com-pared between each period. | eng |
| dc.language.iso | eng | - |
| dc.publisher | Springer Singapore | - |
| dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04466%2F2020/PT | - |
| dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00315%2F2020/PT | - |
| dc.rights | openAccess | - |
| dc.subject | Text mining | eng |
| dc.subject | Sentiment analysis | eng |
| dc.subject | Tourism | eng |
| dc.subject | Hotel traveler’s online reviews | eng |
| dc.subject | COVID-19 pandemic | eng |
| dc.title | Sensing the impact of COVID-19 restrictions from online reviews: The cases of London and Paris unveiled through text mining | eng |
| dc.type | conferenceObject | - |
| dc.event.title | Proceedings of ICMarkTech 2021 | - |
| dc.event.type | Conferência | pt |
| dc.event.location | La Laguna | eng |
| dc.event.date | 2021 | - |
| dc.pagination | 223 - 232 | - |
| dc.peerreviewed | yes | - |
| dc.journal | Marketing and Smart Technologies. Smart Innovation, Systems and Technologies | - |
| dc.volume | 279 | - |
| degois.publication.firstPage | 223 | - |
| degois.publication.lastPage | 232 | - |
| degois.publication.location | La Laguna | eng |
| degois.publication.title | Sensing the impact of COVID-19 restrictions from online reviews: The cases of London and Paris unveiled through text mining | eng |
| dc.date.updated | 2022-05-19T15:28:09Z | - |
| dc.description.version | info:eu-repo/semantics/acceptedVersion | - |
| dc.identifier.doi | 10.1007/978-981-16-9268-0_18 | - |
| dc.subject.fos | Domínio/Área Científica::Ciências Sociais::Economia e Gestão | por |
| dc.subject.fos | Domínio/Área Científica::Ciências Sociais::Geografia Económica e Social | por |
| iscte.subject.ods | Indústria, inovação e infraestruturas | por |
| iscte.identifier.ciencia | https://ciencia.iscte-iul.pt/id/ci-pub-85986 | - |
| Appears in Collections: | ISTAR-CRI - Comunicações a conferências internacionais | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| conferenceobject_85986.pdf | Versão Aceite | 312,64 kB | Adobe PDF | View/Open |
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