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 softwa...

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Bibliographic Details
Published inJournal of Advanced Computational Intelligence and Intelligent Informatics Vol. 29; no. 2; pp. 417 - 422
Main Authors Meng, Lianchao, Chen, Jingjing, Song, Jian, Sun, Guoxia
Format Journal Article
LanguageEnglish
Published Tokyo Fuji Technology Press Ltd 20.03.2025
富士技術出版株式会社
Fuji Technology Press Co. Ltd
Subjects
5A-level tourist attractions
Feedback
Informatics
online reviews
Quality of service
Semantics
Sentiment analysis
sentiment analysis of texts
Software
Tourism
Tourist attractions
Words (language)
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Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1343-0130
1883-8014
DOI:10.20965/jaciii.2025.p0417