Patent Keyword Analysis Using Bayesian Factor Analysis and Social Network Visualization in Digital Therapy Technology

Patent keyword analysis involves extracting and examining keywords from patent documents. Since patents contain detailed information about technologies, analyzing them can provide valuable insights for efficient technology management. This paper proposes a novel method for patent keyword analysis that integrates Bayesian factor analysis and social network visualization. Using Bayesian factor analysis, we extract factors representing key technologies within a domain. These factors are used as nodes in a social network analysis to explore their interrelationships. The resulting visualization aids in constructing a technology diagram, enhancing understanding of the technological structure. To evaluate the method, we analyze patents related to digital therapeutic technologies. Experimental results demonstrate the approach’s effectiveness and its applicability to practical technology analysis tasks. Our results indicate that data analysis serves as a core technology in the field of digital therapy, while technologies such as remote patient monitoring, device systems, and signal processing function as supporting technologies for data analysis. The findings contribute to technology management practices, including strategy development, by analyzing target technologies and deriving actionable insights across various domains, including digital therapeutics.