Sentiment Analysis of Online Reviews for 5A-Level Tourist Attractions

Abstract

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.