STUDY OF TOURIST SATISFACTION AT BUSAN’S TEMPLES: A QUANTITATIVE TEXT MINING APPROACH

Abstract

This study leverages big data analytics to provide a comprehensive analysis of tourist satisfaction at temples in Busan through the examination of online reviews. Utilizing quantitative textual analysis, including frequency analysis, co-occurrence network analysis, and cluster analysis, the research identifies both positive and negative aspects of the temple tourist experience. While visitors frequently highlight the beauty, ambiance, and convenience of temple visits, challenges such as accessibility issues and admission pricing also emerge. This dual perspective offers a balanced view of the tourist experience. The study is notable for its application of advanced text mining tools to a significant dataset, setting it apart from previous research on temple tourism in Busan. The findings underscore the importance of maintaining the temples’ aesthetic appeal and accessibility while addressing tourists' concerns to enhance overall satisfaction. These insights are crucial for temple management and stakeholders in the religious tourism sector, providing a foundation for strategic improvements and a deeper understanding of visitor needs and expectations.