Customer Insight Analysis with Sentiments and Topic Modeling from Wellness Centers in Phuket

The wellness tourism sector has seen rapid growth, making it an essential component of global tourism, particularly in destinations like Phuket, Thailand, known for its holistic wellness programs. This study aims to analyze customer insights derived from online reviews of wellness centers in Phuket using natural language processing (NLP) techniques. We collected reviews from established wellness centers listed on Google Maps and TripAdvisor and employed sentiment analysis using TextBlob to classify customer reviews into positive, negative, or neutral sentiments. In addition, we used supervised topic modeling to categorize reviews into predefined wellness dimensions, including physical, mental, spiritual, emotional, social, and environmental wellness. The analysis showed that most of the reviews are mainly positive, with physical and mental wellness being the topics most frequently discussed. However, there are areas for potential service improvement, particularly in environmental and social wellness. Rather than focusing on developing or comparing machine learning models, this work provides key recommendations for wellness centers to refine their programs and align with customer preferences.

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Published
2024-11-06
DOI
https://doi.org/10.1109/icsec62781.2024.10770722
Primary Topic
Diverse Approaches in Healthcare and Education Studies
Type
article
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article

Customer Insight Analysis with Sentiments and Topic Modeling from Wellness Centers in Phuket

Nattapong Tongtep, K. Bø, Katekanok Kamonmarttayakul
Diverse Approaches in Healthcare and Education Studies
article

Customer Insight Analysis with Sentiments and Topic Modeling from Wellness Centers in Phuket

Nattapong Tongtep, K. Bø, Katekanok Kamonmarttayakul
article en

Abstract

The wellness tourism sector has seen rapid growth, making it an essential component of global tourism, particularly in destinations like Phuket, Thailand, known for its holistic wellness programs. This study aims to analyze customer insights derived from online reviews of wellness centers in Phuket using natural language processing (NLP) techniques. We collected reviews from established wellness centers listed on Google Maps and TripAdvisor and employed sentiment analysis using TextBlob to classify customer reviews into positive, negative, or neutral sentiments. In addition, we used supervised topic modeling to categorize reviews into predefined wellness dimensions, including physical, mental, spiritual, emotional, social, and environmental wellness. The analysis showed that most of the reviews are mainly positive, with physical and mental wellness being the topics most frequently discussed. However, there are areas for potential service improvement, particularly in environmental and social wellness. Rather than focusing on developing or comparing machine learning models, this work provides key recommendations for wellness centers to refine their programs and align with customer preferences.

Prince of Songkla University (TH)
Decent work and economic growth
Openalex Percentile: Top 67%
Diverse Approaches in Healthcare and Education Studies
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