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Analysing the causes of tourists' emotional experience related to tourist attractions from a binary emotions perspective utilising machine learning models
- Yin, Xiaoyan;
- Jung, Taeyeol
Citations
WEB OF SCIENCE
13Citations
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16초록
This study constructs a theoretical framework to analyse the causes of tourists' binary emotional experiences. It applies Support Vector Machine (SVM) and Latent Dirichlet allocation (LDA) machine learning models, combined with geospatial analysis methods, to online reviews of five types of tourist attractions in Dali, China. The results indicate that positive sentiments predominated across Dali Prefecture, though some attractions in Dali City received negative ratings. Furthermore, service experience and price were common influences on tourists' sentiments. This study reveals the causes of tourists' varied emotional experiences at tourist attractions from a binary emotional perspective.
키워드
Emotional experience; Latent Dirichlet allocation; online reviews; sentiment analysis; Support Vector Machine; topic modelling; SERVICE QUALITY; SATISFACTION; REVIEWS; DESTINATION; HAPPINESS; RATINGS; INTENTION; SENTIMENT; VACATION; AIRBNB
- 제목
- Analysing the causes of tourists' emotional experience related to tourist attractions from a binary emotions perspective utilising machine learning models
- 저자
- Yin, Xiaoyan; Jung, Taeyeol
- 발행일
- 2024-06-02
- 유형
- Article
- 권
- 29
- 호
- 6
- 페이지
- 699 ~ 718
- 언어
- ENG
- 출판사
- ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
- 발행국가
- 영국
- 분량
- 20 페이지
- ISSN
- E 1741-6507
P 1094-1665