基于结构熵的科学突破主题识别——以基因工程疫苗领域为例  

Identifying Scientific Breakthrough Topics Using Structure Entropy: Taking the Study Field of Genetic Engineering Vaccines as an Example

作　　者：罗瑞 许海云 刘亚辉[1,2] Luo Rui

机构地区：[1]中国科学院成都文献情报中心,四川成都610041 [2]中国科学院大学经济与管理学院图书情报与档案管理系,北京100190 [3]山东理工大学管理学院,山东淄博255049 [4]中国科学技术信息研究所,北京100038

出　　处：《情报理论与实践》2021年第5期106-114,99,共10页Information Studies:Theory & Application

基　　金：国家自然科学基金项目“基于科学—技术主题关联分析的创新演化路径识别方法研究”(项目编号:71704170);国家重点研发计划项目课题“颠覆性技术地平线扫描系统”(项目编号:2019YFA0707202-01);中国博士后科学基金资助项目“面向多关系融合的知识创新路径的识别与预测方法研究”(项目编号:2016M590124)的成果。

摘　　要：[目的/意义]科学突破主题是对领域发展起关键性作用的主题,对此类主题的发展规律进行探索有助于展开后续识别与预测工作,可更早地进行科学布局,优化科技决策。[方法/过程]文章以基因工程疫苗领域(GEV)为例开展实证研究。从科学突破主题会对知识网络状态带来影响这一基本点切入,以主题词共现网络表征知识网络,首先利用结构熵对知识网络的状态进行测度;之后挖掘对知识网络状态影响较大的主题,作为科学突破主题的候选项;最后借助专家和既有科学成果评估方法的识别效果。[结果/结论]以结构熵测度知识网络的整体性变化,适用于科学突破主题的识别,但其效果的稳定性以及是否具备领域迁移性有待进一步验证。[Purpose/significance] Scientific breakthroughs play a key role in the development of the discipline.Exploring the development laws of such topics will help to carry out subsequent identification and prediction, and can make scientific layout earlier and optimize scientific and technological decisions.[Method/process] This article took the field of genetic engineering vaccines(GEV) as an example to carry out empirical research.Starting from the basic point that scientific breakthrough topics will affect the state of the knowledge network, the topic words co-occurrence network is used to represent the knowledge network, and the structure entropy is used to measure the state of the knowledge network.Afterwards, discover topics that have a greater impact on the state of the knowledge network, as candidates for scientific breakthrough topics, and identify the effects with the help of experts and existing scientific evaluation methods.[Result/conclusion] The structure entropy index is used to measure the overall change of the knowledge network, which is suitable for the identification of scientific breakthrough topics, but the stability of its effect and whether it can be used in other fields needs further verification and exploration.

关 键 词：结构熵 科学突破 知识网络 主题识别 科学预测 

分 类 号：R392[医药卫生—免疫学] G353.1[医药卫生—基础医学]