摘要
[目的/意义]颠覆性技术具有前瞻性、突变性与革命性等特征,对于国家科技创新发展具有巨大的推动作用,在各国的科技研发体系中逐渐占有重要的战略位置。当前各国政策文本数量庞大、主题繁多,传统的情报分析方法难以实现大量政策跟踪与内容挖掘。通过大量政策文本进行主题抽取,可以快速了解其他国家在相关领域的政策倾向与关注焦点。[方法/过程]文章采用word2vec和LDA相结合的主题模型分析技术,对3个国家政府和组织官网公开的颠覆性技术相关的11686条政策文本数据进行主题抽取,通过对主题建模结果的解读,分析欧盟、英国、美国颠覆性技术相关政策文本的主题特征。[结果/结论]研究发现,这些国家和组织在颠覆性技术识别与政策支持方面已经有较为体系化的运转模式,同时对颠覆性技术在计算机科学、信息科学、生命科学、材料与能源、医疗、教育等领域内产生的影响给予了较高关注,且在近几年中普遍倾向于关注国际上达成共识的全球性问题。
[Purpose/significance]With the characteristics of perspectiveness,mutagenicity,and revolutionary,disruptive technology plays a great role in promoting the development of national scientific and technological innovation,and gradually occu-pied an important strategic position in the research and development of various countries.Due to the large number and various top-ics,traditional methods of intelligence analysis are obviously insufficient in solving a large number of policy tracking and content mining.Topic extraction through a large number of policy texts can quickly understand the policy tendencies and focus of other coun-tries in related fields.[Method/process]This paper adopts the topic modeling combining word2vec and LDA to extract topics of the 11686 policy texts related to disruptive technologies published on the official websites of the governments and organizations of three countries.Through the interpretation of the topic modeling results,the characteristics of the EU,the United Kingdom and the Unit-ed States are analyzed.[Result/conclusion]Through the analysis of this paper,European and American countries have a relative-ly systematic operation mode in terms of disruptive technology identification and policy support.At the same time,they pay more at-tention to the impact of disruptive technology in computer science,information science,biological science,material and energy,medicine and pharmacy,education and other fields.In recent years,the role of disruptive technology in solving global problems that have reached international consensus has received widespread attention.
出处
《情报理论与实践》
CSSCI
北大核心
2022年第6期39-47,共9页
Information Studies:Theory & Application
基金
国家社会科学基金项目“基于多源数据融合的情报用户需求探测研究”的成果,项目编号:17BTQ066。
