摘要：

【目的】 针对当前我国在学科交叉特征研究中的不足,建立一套规则、结构清晰的学科交叉特征识别方法。【方法】 以Web of Science数据库收录的生物医学工程领域论文所属期刊的学科分类为数据基础,通过引入中介中心性、度中心性、信息熵指标,利用学科共现分析方法,结合Bibexcel、Ucinet社会网络分析软件建立学科关联网络图谱,识别生物医学工程领域学科交叉的结构演化特征,验证了其在学科交叉特征识别中的可行性。【结果】 分析生物医学工程领域的学科交叉特征,得出该领域的亲缘学科,结果表明“生物医学工程”研究领域的信息熵随着时间的演进而增大,说明该领域的学科交叉程度愈加深入。【结论】 实验结果与实际情况较为一致,验证了学科交叉特征识别方法的可靠性。

关键词: 学科交叉, 中心性, 信息熵

Abstract:

[Purposes] In view of deficiency in current research on cross disciplinary characteristics in China, this paper aims to establish a set of rules and structures of interdisciplinary feature identification. [Methods] The data based on subject category of biomedical engineering were collected from the Web of Science database. The paper introduced betweenness centrality, degree centrality, and Shannon entropy and took advantage of Bibexcel and Ucinet, social network analysis software, to establish interdisciplinary network map based on subject co-occurrence analysis. Structure and evolution characteristics in biomedical engineering were identified and feasibility in interdisciplinary feature identification were verified. [Findings] Related subjects can be found by analysis of its interdisciplinary feature identification. The results show that the information entropy in biomedical engineering increases with the evolution of time, which indicates that the degree of interdisciplinary integration in this field is further deepened. [Conclusions] The result is consistent with the actual situation, which verifies the reliability of the method.

Key words: Interdiscipline, Centrality, Shannon entropy