Sentiment Analysis of Online Reviews for 5A-Level Tourist Attractions
This study aims to explore tourists’ sentiment tendencies and focal points by analyzing online reviews of 5A-level tourist attractions. After conducting data cleaning, word segmentation, stop-word filtering, and part-of-speech tagging, we preprocessed the review texts and utilized the ROSTCM6 software for sentiment analysis. The study found that most tourists hold a positive attitude toward their experiences at 5A-level attractions, though there remains room for improvement in certain facilities and services. This research provides valuable feedback for attraction managers to enhance the visitor experience.
Authors
- Lianchao Meng
- Guoxia Sun
- Jingjing Chen (ORCID: https://orcid.org/0000-0003-3148-264X)
- Jian Song (ORCID: https://orcid.org/0000-0003-1635-1801)
Institutions
- Jilin University (CN)
- Changchun University (CN)
Publication Details
- Journal
- Journal of Advanced Computational Intelligence and Intelligent Informatics
- Published
- 2025-03-19
- DOI
- https://doi.org/10.20965/jaciii.2025.p0417
- Citations
- 1
- Primary Topic
- Digital Marketing and Social Media
- Type
- article
- Field-Weighted Citation Impact
- 4.20