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

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.