Harnessing Social Media Data for Sentiment Analysis of Tourist Attractions in Trat Province, Thailand using the Random Forest Machine Learning Approach

Tourism and service industries are vital economic drivers worldwide, and social media platforms play a pivotal role in disseminating and gathering tourist reviews. This study employed the random forest algorithm to analyze tourist reviews of attractions in Trat Province, Thailand, using data collected from the Tripadvisor website between 2014 and 2023. From the results, key issues impacting these destinations were identified and categorized into four main areas, i.e., scenery, facilities, safety, and accessibility. With a high accuracy rate of 99.65%, the analysis revealed that 98.66% of the reviews reflected positive sentiment, underscoring the province’s appeal. However, the findings of this study also highlight critical challenges, particularly in terms of facilities and safety, which require attention to realize sustainable tourism management. The findings provide valuable insights for stakeholders to enhance the quality of tourism services in Trat, aligning with the province’s aspirations to elevate its status to a primary tourist destination in Thailand.