基于CiteSpace的技术预测研究的可视化分析  

Visual Analysis about the Research of Technology Forecasting Based on CiteSpace

作　　者：王翠波[1] 熊坤 刘文俊[1] Wang Cuibo;Xiong Kun;Liu Wenjun(School of Management,South‐Central University for Nationalities,Wuhan 430074,China)

机构地区：[1]中南民族大学管理学院,武汉430074

出　　处：《技术经济》2020年第6期147-154,共8页Journal of Technology Economics

基　　金：国家社会科学基金青年项目“基于实时大数据的潜在新兴技术敏捷预测机制研究”(14CTQ017)。

摘　　要：基于科学知识图谱软件CiteSpace,对从中国知网(CNKI)数据库中获取的技术预测科学文献,从文献维度、内容维度等角度进行可视化共现及聚类分析,探索技术预测研究现状及发展趋势。相关分析表明:①技术预测合作研究主要限于学科领域内部;②技术预测研究方法主要包括TRIZ理论、文献计量、文本挖掘和知识图谱等,呈现出从定性向定量、从数字化向知识化发展的特征;③技术预测研究方向主要包括新兴技术主题识别、技术机会识别、颠覆性技术预测、技术态势探索等,呈现出深化实证应用的发展趋势。This paper aims to explore the status quo and trends of technology forecasting(TF)research. Literatures about TF are extracted from CNKI and imported into CiteSpace. Based on CiteSpace,the scientific knowledge map software,the paper carries out visual co-occurrence and cluster analysis from the perspectives of document dimensions and content dimensions. The results show as follows. The cooperative researches in TF are almost limited to the same discipline. The research method about TF mainly includes TRIZ theory,Bibliometrics,text mining and knowledge map,and reflects the development characteristics from qualitative to quantitative and then from digital to knowledge. The research direction of TF mainly includes topic identification of emerging technology,technology opportunity discovery,disruptive technology forecasting and situation exploration,and reflects the development trend of deepening empirical application.

关 键 词：技术预测 科学知识图谱 CITESPACE 可视化分析 

分 类 号：G321.9[文化科学]