Understanding Tourist Sentiment and Feedback: An Integrated Approach Using Deep Learning Model in Scenic Areas

This paper proposes a framework for sentiment analysis of tourists, comprehensively analyzing the aspect-level sentiment and descriptive statements of tourists in the tourism field. Firstly, we introduce the InstructABSA deep learning model, utilized for analyzing the aspect-level sentiment of tourists in scenic areas. Next, we discuss methods of text clustering analysis and keyword analysis to better understand the semantic information in tourist comments. Through experimental and conclusion sections, we summarize the sentiment tendencies and descriptive statements of tourists in scenic areas, delving into their views and feelings about the tourist experience. In summary, this study provides a comprehensive understanding of tourist sentiments and comments in scenic areas, offering valuable insights for scenic area management and improvement.