基于自然指数刊文数据对全球医学研究领域热点的探析  

Analysis of Research Hotspots in the Field of Global Medical Research Based on Natural Index

作　　者：杨颖[1] 许丹[1] 陈斯斯[1] 韩爽[1] 徐爽[1] Yang Ying;Xu Dan;Chen Sisi;Han Shuang;Xu Shuang(Library of China Medical University,Shenyang 110122)

机构地区：[1]中国医科大学图书馆

出　　处：《情报学报》2019年第11期1129-1137,共9页Journal of the China Society for Scientific and Technical Information

基　　金：辽宁省教育厅科学研究一般项目“大数据时代高校图书馆面向重点学科的综合情报服务研究”（W2014106）

摘　　要：自然指数从2014年提出以来,针对既有指标开展的研究如火如荼,但基于其基础数据的科学计量学分析相对匮乏。本文选择全球医学研究领域自然指数期刊为研究对象展开科学计量分析。基于共词分析和社会复杂网络理论,利用科学计量工具BICOMB及Ucinet分析近两年间发文热点的社会网络结构;同时,利用gCLUTO软件对其词篇矩阵进行双向聚类,探索其研究前沿结构构成。研究揭示了全球医学研究领域的热点前沿,为该领域发展方向提供参考,并分析自然指数在评估科研时的优缺点。Since the Natural Index was proposed in 2014, research has progressively increased on existing indicators, but scientometric analysis based on basic data is relatively scarce. Scientific quantitative analysis is based on publications in Natural Index journals in the field of global medical research. Based on the theories of co-word analysis and co-occurrence network, scientific measurement tools such as BICOMB and Ucinet are used to analyze the social network structure of research hotspots of the past two years. Additionally, the gCluto software is used for biclustering the word-article matrix to explore research frontiers. This research reveals the hotspots of global medical research, provides a reference for the development direction of the field, and analyzes the advantages and disadvantages of the Natural Index in the evaluation of scientific research.

关 键 词：医学研究 自然指数 社会网络分析 双聚类 共词分析 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]