비정형 빅데이터를 활용한 ESG 관광활동에 대한 관광객 인식에 관한 연구

The purpose of this study is to explore tourists' perceptions of ESG (Environmental, Social, and Governance) tourism activities by utilizing unstructured big data analysis techniques, especially text mining. This study collected and analyzed data from major portal sites to identify keywords related to ESG tourism, and applied methods such as semantic network and CONCOR analysis to identify central themes and structural relations between keywords. Through frequency and centrality analysis, it was confirmed that they are major topics such as community participation, environmental sustainability, and economic governance. As a result of the study, tourists recognize ESG tourism as a multi-faceted concept that integrates cultural experiences, social responsibility, and economic values, and emphasize the need for customized sustainable tourism initiatives including community participation and transparent management practice. In addition, the importance of experience programs was highlighted to revitalize ESG tourism, and resident participation through interaction with local characteristics and communities was confirmed as an essential factor. These findings suggest policy research directions for sustainable tourism, and provide basic data to explore the relationship between ESG factors by effectively applying ESG principles to tourism.