Understanding cross-cultural destination perceptions through key attraction factors
A dynamic analysis of Chinese tourist experiences in Thailand
Bibliographic Data
| ID | 11410385 |
|---|---|
| Authors | Aniwat Phaphuangwittayakul (0000-0002-2289-3116, Chiang Mai University), Siva Shankar Ramasamy (0000-0002-6160-5949, Chiang Mai University, corresponding author), Fangli Ying (0000-0001-8390-3229, East China University of Science and Technology), Nopasit Chakpitak (0000-0001-9498-5696, Chiang Mai University) |
| Year | 2026 |
| Pages | 1-19 |
| Publication date | 2026-02-12 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Tourism Recreation Research (JOURNAL) |
| Journal identifiers | ISSN: 0250-8281 • E-ISSN: 2320-0308 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/02508281.2025.2611764 |
| OpenAlex | W7128730269 |
| Language | EN |
| References cited | 56 |
Understanding the behavior and satisfaction of tourists is crucial for maintaining the quality of tourism experiences and improving local products and services. However, existing methods for extracting semantic information and sentiment have limitations. This paper proposes a novel approach to extract topics and sentiments from comments on a Chinese social media platform. This method combines hybrid topic extraction and dynamic sentiment analysis models to identify attraction factors. It shows significant improvement in the topic extraction task and provides sentiment scores more efficiently across different time frames. Using this combination, the method identifies key attraction factors that most influence tourists. The results show that Tourism Activities emerges as the most influential attraction factor, while Accessibility and Mobility receive the most negative sentiments. This information can help practitioners in the tourism industry, including local business owners or government agencies, develop strategies to enhance products or services associated with each attraction factor across different time periods based on their sentiment scores. Moreover, this approach can be further developed for application to other tourism destinations.
Attraction · Destinations · Key (lock · Perception · Tourism · Tourist attraction · Culinary Culture and Tourism · Diverse Aspects of Tourism Research · Religious Tourism and Spaces
Wordnet
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Transformers
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Exploring the Space of Topic Coherence Measures
Enotourist satisfaction
The Measurement of Destination Image
Cross-Cultural Validation of a Memorable Tourism Experience Scale (MTES)
Analyzing online reviews of foreign tourists to destination attractions in China
Little-known leisure places
Automated topic modeling of tourist reviews
Structural Topic Models for Open‐Ended Survey Responses
| Citation velocity | historical |
|---|---|
| Highly cited | No |