Sensing the impact of COVID-19 restrictions from online reviews: The cases of London and Paris unveiled through text mining

• Autor(a) principal: Silva, Bruno Rafael Martins da
• Data de Publicação: 2021
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10071/23879
• topic: Text mining; Sentiment analysis; Tourism; Hotel traveller’s online reviews; COVID-19; Análise de sentimento; Turismo; Análises online de hotéis de viajantes

This study aims to understand how the COVID-19 pandemic affected the hotel sector and to identify the current traveler demands. The traveler’s reviews were analyzed based on a sentiment and guest satisfaction analysis, 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. The data collection consisted in a dataset of 8k reviews from 226 hotels in total. Text data were extracted from reviews made in two time periods, before and during the COVID-19 pandemic. The sentiment and specific aspects highlighted by travelers were compared between each period. This analysis may also serve as a basis for other studies aimed at a better understanding of the behavior of hotel guests during the COVID-19 pandemic.