基于动态结构熵的颠覆性技术知识网络扩散特征识别方法研究  

Research on the Method of Identifying Disruptive Technology Knowledge Networks Diffusion Characteristics Based on Dynamic Structure Entropy

作　　者：王超[1,3] 许海云 武华维 齐砚翠 陈亮 Wang Chao;Xu Haiyun;Wu Huawei;Qi Yancui;Chen Liang(Business School,Shandong University of Technology,Zibo 255000;Library of Shandong Normal University,Jinan 250014;Archives of Northwestern Normal University,Lanzhou 730070;Institute of Scientific and Technical Information of China,Beijing 100038)

机构地区：[1]山东理工大学管理学院,淄博255000 [2]西北师范大学档案馆,兰州730070 [3]山东师范大学图书馆,济南250014 [4]中国科学技术信息研究所,北京100038

出　　处：《图书情报工作》2023年第24期54-71,共18页Library and Information Service

基　　金：国家自然科学基金项目“基于弱信号时效网络演化分析的变革性科技创新主题早期识别方法研究”(项目编号:72274113);山东省自然科学基金项目“基于弱信号分析的变革性创新主题早期识别方法研究”(项目编号:ZR202111130115)研究成果之一。

摘　　要：[目的/意义]利用动态结构熵探究颠覆性技术知识网络扩散过程中的结构变化并识别网络结构变化过程中的突变状态,以此发现颠覆性技术知识网络扩散特征,为颠覆性技术的早期识别提供方法借鉴。[方法/过程]首先,构建颠覆性技术在基础研究、应用研究、产业应用创新过程环节中的3种动态知识子网络;其次,利用动态结构熵探究颠覆性技术知识网络扩散特征;之后,通过突变函数模型分析颠覆性技术知识网络扩散过程中的结构突变特征;最后,利用动态时间规整法探析颠覆性技术各知识子网络间扩散的相关性及其与渐进性技术扩散特征的差异性。[结果/结论 ]实证研究表明利用提出的动态结构熵开展颠覆性技术知识网络扩散特征识别,能够发现颠覆性技术分别在基础研究、应用研究、产业应用知识子网络的微观结构、介观结构、微观与介观结构关系与网络结构突变等方面知识网络扩散特征,并通过3种网络扩散特征的综合分析,解析出颠覆性技术显著区别于渐进性技术的网络扩散特征。[Purpose/Significance] This research utilizes dynamic structural entropy to explore the structural changes in the diffusion process of disruptive technology knowledge networks and to identify mutation states during network structural changes. This approach aims to uncover the diffusion characteristics of disruptive technological knowledge networks, providing a methodological reference for the early identification of disruptive technologies.[Method/Process] Three dynamic knowledge sub-networks first are constructed for disruptive technology in the stages of basic research, applied research, and industrial application innovation. Secondly, dynamic structural entropy is employed to investigate the diffusion characteristics of disruptive technology knowledge networks. Subsequently, structural mutation features in the diffusion process of disruptive technology knowledge networks are analyzed using a mutation function model. Finally, the dynamic time warping method is employed to analyze the correlation of diffusion among different knowledge sub-networks of disruptive technologies and to highlight the differences between their diffusion characteristics and those of incremental technologies. [Result/Conclusion]Empirical research demonstrates that the proposed dynamic structural entropy to identify diffusion characteristics of disruptive technology knowledge networks can reveal diffusion features in the knowledge sub-networks of basic research, applied research, and industrial application in terms of micro-structure, meso-structure, the relationship between micro and meso-structures, and network structural mutation. Through the comprehensive analysis of three diffusion characteristics, the distinct diffusion features of disruptive technology as compared to incremental technologies are deciphered.

关 键 词：颠覆性技术 动态结构熵 知识网络 技术扩散 结构突变 

分 类 号：G250[文化科学—图书馆学]