텍스트마이닝을 활용한 학술지 『한국고지도연구』 연구동향 분석

초록

This study examines research trends in 187 articles published in the Journal of the Korean Research Association of Old Maps between 2009 and 2025 through quantitative and text-mining techniques. The methods include publication and author analysis, citation analysis, keyword frequency analysis, TF-IDF, keyword network analysis, and LDA topic modeling. The results showed a steady increase in both the number of published articles and authors. Strong interdisciplinary links were identified, particularly between geography and related fields such as history. In addition, the citation half-life in this field was comparatively longer than those in other academic disciplines. Keyword analysis highlighted “Joseon,” “production,” and “place names” as core terms. Furthermore, keyword network analysis revealed clusters centered on the Joseon period and Japan, while topic modeling identified five major themes, including place names and territorial awareness, spatial perception, and cartographic representation styles. This study is significant because it complements previous research with a data-driven approach. The findings provide foundational data for selecting topics and setting research directions in future studies on old maps.

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