Smart factory technology, a core component of the Fourth Industrial Revolution, demonstrates significant disparities in technological development across countries. To quantitatively assess these international technology gaps, this study proposes an integrated analytical framework that combines text mining-based topic modeling and social network analysis (SNA), using global smart factory-related patent data from 2017 to 2023. Approximately 4,300 patent documents (titles and abstracts) were collected through the GPASS system and preprocessed. Through Latent Dirichlet Allocation (LDA) modeling with optimized hyperparameters, major technology topics were identified. Semantic interpretation using ChatGPT and expert review enabled the assignment of precise topic labels, which were further mapped to CPC (Cooperative Patent Classification) codes to construct a standardized technology taxonomy. Subsequently, the network structures of topic and classification nodes were analyzed by country (China, the United States, and South Korea), and the relative importance of key technology areas was evaluated using centrality metrics such as degree, closeness, betweenness, and eigenvector centrality. The analysis revealed that, globally, the most central technology areas include manufacturing process management and control, IoT and data-driven decision making, and facility-based process optimization. At the national level, China showed a strategic focus on technologies related to product quality improvement and cost reduction, South Korea emphasized IoT-enabled technologies and equipment-level optimization, while the United States prioritized control systems and data-driven project management. By utilizing patent-based textual data, this study offers a novel methodology for quantitatively diagnosing structural differences in national technological capabilities. The proposed framework provides valuable insights for country-specific R&D planning and strategic decision-making in the field of smart manufacturing.

1. 서 론
2. 선행 연구
    2.1 스마트팩토리 기술 관련 연구
    2.2 특허 기반 기술분석 및 토픽모델링 관련 연구
    2.3 사회연결망분석(SNA)을 활용한 기술 구조 분석
3. 연구 방법론
    3.1 연구방법론 설계
    3.2 데이터 구성
    3.3 토픽 모델링 분석
    3.4 CPC 연계 분석
    3.5 사회 연결망 분석(SNA)
4. 연구 결과
    4.1 토픽 모델링 결과 및 기술 주제 해석
    4.2 기술 주제와 CPC 코드 간 연계 분석
    4.3 국가별 기술 네트워크 구조 분석(SNA)
    4.4 중심성 분석을 통한 기술 주제 비교
5. 결 론
Acknowledgement
References

• Sanggook Kim(Global R&D Analysis Center, Korea Institute of Science and Technology Information) | 김상국 (한국과학기술정보연구원 글로벌R&D분석센터) Corresponding author
• Taehoon Kwon(Global R&D Analysis Center, Korea Institute of Science and Technology Information) | 권태훈 (한국과학기술정보연구원 글로벌R&D분석센터)