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
Inglese
28th International Conference on IT Applications and Management
Korea Database Strategy Society (KDSS)
Anamnagar, Kathmandu-29,
NEPAL
Sateesh Kumar Ojha (Lincoln University, Malaysia)
176
178
3
ITAM28, Data-centered Collaboration for enhanced social capability
Contributo
Esperti anonimi
21-24 febbraio 2024
Dayeh University, Changhua; Taiwan
internazionale
scientifica
Tourism satisfaction; Online Review, electronic-word-of-mouth (e-WOM); natural language processing;
Goal 11: Sustainable cities and communities
no
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Dessi', Cinzia; Ortu, Marco; Massidda, Carla; Contu, Giulia
273
4
4.1 Contributo in Atti di convegno
none
info:eu-repo/semantics/conferencePaper
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