Work

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

Year: 2025

Type: article

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.

Source: Journal of Advanced Computational Intelligence and Intelligent Informatics

DOI: 10.20965/jaciii.2025.p0417

Authors: Lianchao Meng, Jingjing Chen, Jian Song, Guoxia Sun

Institutions: The Tourism College of Changchun University, Changchun University, Jilin Business and Technology College, Jilin University

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4408613595

FWCI: 1.709

Cites:

Cited by: 4

Related to: 10