Sensing the Impact of COVID-19 Restrictions from Online Reviews: The Cases of London and Paris Unveiled Through Text Mining
Smart Innovation, Systems and Technologies
; 279:223-232, 2022.
Article
in English
| Scopus | ID: covidwho-1787786
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 reviews 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 pandemic. The sentiment and specific aspects highlighted by travelers were compared between each period. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
Language:
English
Journal:
Smart Innovation, Systems and Technologies
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS