Technology Forecasting based on Topic Analysis and Social Network Analysis: A Case Study Focusing on Gene Editing Patents

Abstract

Technology forecasting research is an indispensable means to master the development trend of technology and provide decision support for scientific research management. For patent documents, it does not provide keyword information, which makes the keyword based technology prediction method have some limitations in revealing research content and hidden topics in specific fields. In order to better reflect the technical information in the patent, this paper combines topic analysis and social network analysis to study the development trends of gene editing technology. First, the patent data of gene editing technology is collected from Derwent Innovations Index. Secondly, text mining software is adopted to draw a network graph of topic words, combined with Inverse Document Frequency (IDF) to construct a weighted adjacency matrix, and Social Network Analysis is used to obtain the degree of centrality of technical topic words. Finally, the technological trends of gene editing technology is explored by identifying the core themes of gene editing, highlighting themes and emerging themes, and some meaningful conclusions are also obtained. Based on the analysis results, this study finds that the development of gene editing technology is limited by factors such as ethics, law and cellular pollution. In addition, future research directions will be more inclined to optimize the safety and efficiency of gene editing technology.