텍스트 마이닝을 활용한 국내 섬 관광 연구동향(2001~2024) 분석

Analyzing Research Trends of Island Tourism in South Korea (2001–2024) Using Text Mining

Island tourism has gained prominence as a growing field in response to shifting tourism demands and government policies. This study analyzes research trends in island tourism by applying text mining techniques to 1,057 academic articles related to ‘island tourism’ and ‘island destinations’ published in KCI-listed journals between 2001 and 2024. The analysis employed methods such as word frequency, TF-IDF, N-gram and CONCOR analysis. Key findings show that terms like ‘region’, ‘culture’, ‘resources’, ‘environment’, ‘policy’, ‘development’ and ‘revitalization’ frequently appeared, highlighting the importance of policy-driven perspectives on tourism resources, development and revitalization. In addition, community-led initiatives, cultural tourism resources and the tourism industry emerged as significant research themes. Based on word association patterns, the study identified seven thematic groups: sustainable island tourism (G1), competitiveness of island destinations (G2), island tourism policy (G3) and enhancement of island tourism resources and values (G4–G7). The results offer foundational insights into the evolution of domestic island tourism research and can serve as a basis for future studies and policy development. Furthermore, this study demonstrates the methodological utility of text mining for analyzing unstructured textual data in tourism research.