Abstract

Purpose: This study aims to examine hotel reviews, with a specific emphasis on environmental aspects. Employing advanced sentiment analysis techniques, we delve into user sentiments expressed in evaluations. Theoretical Framework: The theoretical framework utilizes sentiment analysis to delve into hotel reviews, emphasizing the environment. Focused on key areas such as staff service (professionalism and friendliness), hotel environment and facilities (beautiful décor and cleanliness), and affordability with a friendly pricing strategy. Design/Methodology/Approach: This study involves the manual collection and analysis of 3,475 hotel review from Centara Hotel & Convention Center Udon Thani. The methodology includes systematic steps: Preprocessing (removing irrelevant charcters and stopword), Feature Extraction (identifying key elements), Classification (using Logistic Regression for binary sentiment analysis), and Prediction (applying the model to categorize new reviews). Findings: In our findings, Logistic Regression effectively categorized reviews into positive or negative sentiments, boasting a robust macro precision of 0.80. Notably, positive evaluations showed superior prediction results, with a high recall value of 0.84 percent, contributing to an impressive overall accuracy of 86 percent. These results highlight the efficacy of Logistic Regression in distinguishing sentiment categories, affirming its suitability for this analysis. Research, Practical & Social Implications: In summary, focusing on enhancing staff service, maintaining a pristine hotel environment, and offering friendly, affordable services has the potential to greatly boost customer satisfaction and overall business performance. These strategic efforts not only generate positive feedback but also lead to increased competitive advantages and expanded market share in the fiercely competitive hotel industry. Originality/Value: The findings have broader implications by shaping public perceptions, providing valuable insights for strategic decision-making, and positioning hotels for success in the highly competitive hospitality landscape.

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