Enhancing tourism facility competitiveness demands methods for accurately measuring tourist satisfaction. Positive visitor experiences contribute to regional development and business sustainability by encouraging spending, repeat visits, and enhancing destination reputation. This study utilizes natural language processing and Sentiment Analysis to scrutinize online reviews, aiming to pinpoint factors affecting satisfaction differences between inland and coastal destinations, with subsequent discussions on implications for academia and management.

Tourism Management and Customers' Satisfaction: A Natural Language Processing and Machine Learning Framework

DESSI CINZIA
Secondo
;
MARCO ORTU
Ultimo
;
CARLA MASSIDDA
Penultimo
;
GIULIA CONTU
Primo
2024-01-01

Abstract

Enhancing tourism facility competitiveness demands methods for accurately measuring tourist satisfaction. Positive visitor experiences contribute to regional development and business sustainability by encouraging spending, repeat visits, and enhancing destination reputation. This study utilizes natural language processing and Sentiment Analysis to scrutinize online reviews, aiming to pinpoint factors affecting satisfaction differences between inland and coastal destinations, with subsequent discussions on implications for academia and management.
2024
Tourism satisfaction; Online Review, electronic-word-of-mouth (e-WOM); natural language processing;
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/406164
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