Abstract

This study analyzed 534 academic papers published in Korea on K-SDGs (Korean Sustainable Development Goals) from 2015 to 2024 to identify overall research trends and key thematic characteristics of K-SDGs studies. To achieve this objective, a comprehensive quantitative and qualitative integrated analysis was conducted, employing keyword network analysis, SBERT (Sentence-BERT)-based SDG automatic mapping, and manual mapping by researchers. The keyword network analysis revealed “Sustainable Development Education,” “ODA (Official Development Assistance),” “ESG (Environmental, Social, and Governance),” and “VNR (Voluntary National Review)” as prominent keywords. Specifically, the co-occurrence network analysis of keywords appearing four or more times indicated that “Sustainable Development Education” served as a central hub. The SBERT-based SDG automatic mapping showed that “Goal 17: Partnerships for the Goals” and “Goal 4: Quality Education” accounted for the highest proportion of research topics. Furthermore, comparison with manual mapping results revealed a matching rate of 58.1% for representative SDG targets. When including cases where at least one SDG overlapped among all SDGs, the expanded matching rate reached 82.8%. These findings suggest that SBERT-based automatic analysis can capture the major themes of K-SDGs research with considerable accuracy and can be utilized in a complementary manner with manual analysis by human experts. This study illuminates both the practicality and limitations of automation-based analysis while emphasizing the importance of expert interpretation. It proposes the necessity of adopting an integrated approach that combines quantitative and qualitative analysis in future K-SDGs-related research and policy development processes.