Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/25466
Author(s): Silva, B.
Moro, S.
Marques, C.
Editor: Reis, J. L., Parra López, E., Moutinho, L., and Santos, J. P. M. dos.
Date: 2022
Title: Sensing the impact of COVID-19 restrictions from online reviews: The cases of London and Paris unveiled through text mining
Volume: 279
Pages: 223 - 232
Event title: Proceedings of ICMarkTech 2021
ISSN: 2190-3018
ISBN: 978-981-16-9268-0
DOI (Digital Object Identifier): 10.1007/978-981-16-9268-0_18
Keywords: Text mining
Sentiment analysis
Tourism
Hotel traveler’s online reviews
COVID-19 pandemic
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.
Peerreviewed: yes
Access type: Open Access
Appears in Collections:ISTAR-CRI - Comunicações a conferências internacionais

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