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首页> 外文期刊>Journal of Scientific & Industrial Research >Technology Forecasting based on Topic Analysis and Social Network Analysis: A Case Study Focusing on Gene Editing Patents
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Technology Forecasting based on Topic Analysis and Social Network Analysis: A Case Study Focusing on Gene Editing Patents

机译:基于主题分析和社会网络分析的技术预测 - 以基因编辑专利为例

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摘要

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.
机译:技术预测研究是掌握技术发展趋势的不可或缺的手段,为科研管理提供决策支持。对于专利文献,它不提供关键字信息,这使得基于关键字的技术预测方法具有在特定领域的揭示研究内容和隐藏主题中具有一些限制。为了更好地反映该专利中的技术信息,本文结合了主题分析和社会网络分析,研究了基因编辑技术的发展趋势。首先,从Derwent Innovations指数中收集基因编辑技术的专利数据。其次,采用文本挖掘软件绘制主题词的网络图,与逆文档频率(IDF)组合来构造加权邻接矩阵,并且使用社交网络分析来获得技术主题词的中心地位。最后,通过识别基因编辑的核心主题,突出主题和新兴主题的核心主题探讨了基因编辑技术的技术趋势,并获得了一些有意义的结论。该研究基于分析结果,该研究发现基因编辑技术的发展受伦理,法律和细胞污染等因素的限制。此外,未来的研究方向更倾向于优化基因编辑技术的安全性和效率。

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