국내 인지의미론 연구 동향 및 전망: 생성형 AI 기반 범주화 및 키워드 분석을 중심으로
Trends and Prospects of Cognitive Semantics Research in Korea: Generative AI-Based Categorization and Keyword Analysis
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초록
This study aims to analyze the trends of cognitive semantics research conducted in Korea over the past decade and suggest future research directions based on this analysis. Focusing on the core theories of cognitive semantics— conceptual metaphor, conceptual metonymy, conceptual blending—the study analyzes academic papers published in Korea. Using generative AI tools like ChatGPT for large-scale data analysis, the study categorizes research outcomes and identifies trends in keywords and publication years. The results show that the theory of conceptual metaphor remains a primary research focus, expanding into various fields such as literature, politics, and education. While research on conceptual metonymy and conceptual blending is relatively sparse, the potential for expansion in these areas remains significant. This study proposes specific research directions for broadening the application of these theories, particularly in educational contexts and contrastive studies. Future research should emphasize the application of generative AI and large corpus-based methods to enhance the practical use and theoretical value of conceptual metaphors and metonymies.
Abstract
This study aims to analyze the trends of cognitive semantics research conducted in Korea over the past decade and suggest future research directions based on this analysis. Focusing on the core theories of cognitive semantics— conceptual metaphor, conceptual metonymy, conceptual blending—the study analyzes academic papers published in Korea. Using generative AI tools like ChatGPT for large-scale data analysis, the study categorizes research outcomes and identifies trends in keywords and publication years. The results show that the theory of conceptual metaphor remains a primary research focus, expanding into various fields such as literature, politics, and education. While research on conceptual metonymy and conceptual blending is relatively sparse, the potential for expansion in these areas remains significant. This study proposes specific research directions for broadening the application of these theories, particularly in educational contexts and contrastive studies. Future research should emphasize the application of generative AI and large corpus-based methods to enhance the practical use and theoretical value of conceptual metaphors and metonymies.