이택균 2024-06 1738-6667 https://aurora.ajou.ac.kr/handle/2018.oak/36026 This study aims to analyze research trends in digital twin focusing on Germany, the US, and Korea. In Elsevier's Scopus, we collected 4,657 papers about digital twin published in from 2019 to 2023. Keyword frequency and centrality analysis were conducted on the abstracts of the collected papers. Through the obtained keyword frequencies, we tried to identify keywords with high frequency of occurrence and through centrality analysis, we tried to identify central research keywords for each country. In each country, 'digital_twin', 'machine_learning', and 'iot' appeared as research keywords with the highest interest. As a result of the centrality analysis, research on digital twin, simulation, cyber physical system, Internet of Things, artificial intelligence, and smart manufacturing was conducted as research with high centrality in each country. The implication for Korea is that research on virtual reality, digital transformation, reinforcement learning, industrial Internet of Things, robotics, and data analysis appears to have been conducted with low centrality, and intensive research in related areas appears to be necessary. Kor (사)디지털산업정보학회 키워드 빈도 및 중심성 분석에 기반한 디지털 트윈 연구 동향 : 독일·미국·한국을 중심으로 Research Trend on Digital Twin Based on Keyword Frequency and Centrality Analysis : Focusing on Germany, the United States, Korea Article 25 2 11 (사)디지털산업정보학회 논문지 20 (사)디지털산업정보학회 논문지, Vol.20 No.2, pp.11-25 Digital Twin Trend Centrality Frequency Article