作者分类号耦合分析与作者关键词耦合分析的比较研究
发布时间：2019-05-28 21:52
【摘要】：[目的/意义]作者耦合分析是文献计量学中探测学科知识结构的常用方法之一,作者关键词耦合分析(AKCA)已经获得了广泛应用,但是鲜有作者分类号耦合分析(ACCA)。[方法/过程]以国内图书馆学期刊论文为样本,分别基于中图分类号和关键词两类特征项,构建作者耦合关系网络。采用QAP相关分析、因子分析、社会网络分析及可视化方法,对作者分类号耦合分析和作者关键词耦合分析的效果进行比较。[结果/结论]作者分类号耦合与作者关键词耦合均适用于发掘潜在合作关系。作者分类号耦合分析在网络密度、关系强度、聚类效果等方面,表现出比作者关键词耦合更好的分析效果。两种方法在揭示学科知识结构时各有优劣,无法相互取代。
[Abstract]:[objective / significance] the author's coupling analysis is one of the common methods to detect the knowledge structure of the subject in bibliometrics. The author's keyword coupling analysis (AKCA) has been widely used, but few of the author's classification number coupling analysis (ACCA). [methods / process] taking the papers of domestic library science journals as samples, the author coupling relation network was constructed based on the classification number and keyword of the Chinese map, respectively. QAP correlation analysis, factor analysis, social network analysis and visualization methods were used to compare the effects of author classification number coupling analysis and author keyword coupling analysis. [results / conclusion] the coupling of author classification number and author keyword is suitable for exploring potential cooperative relationship. The author's classification number coupling analysis shows better analysis effect than the author's keyword coupling in terms of network density, relationship strength, clustering effect and so on. The two methods have their own advantages and disadvantages in revealing the knowledge structure of the subject and can not be replaced by each other.
【作者单位】： 河南科技大学管理学院;
【基金】：国家社会科学基金青年项目“面向专利数据的多重共现分析方法及其在技术创新网络中的应用研究”(编号:14CTQ018) 河南省高等学校哲学社会科学研究优秀学者资助项目(编号:2017-YXXZ-07)的成果
【分类号】：G353.1
本文编号：2487387
[Abstract]:[objective / significance] the author's coupling analysis is one of the common methods to detect the knowledge structure of the subject in bibliometrics. The author's keyword coupling analysis (AKCA) has been widely used, but few of the author's classification number coupling analysis (ACCA). [methods / process] taking the papers of domestic library science journals as samples, the author coupling relation network was constructed based on the classification number and keyword of the Chinese map, respectively. QAP correlation analysis, factor analysis, social network analysis and visualization methods were used to compare the effects of author classification number coupling analysis and author keyword coupling analysis. [results / conclusion] the coupling of author classification number and author keyword is suitable for exploring potential cooperative relationship. The author's classification number coupling analysis shows better analysis effect than the author's keyword coupling in terms of network density, relationship strength, clustering effect and so on. The two methods have their own advantages and disadvantages in revealing the knowledge structure of the subject and can not be replaced by each other.
【作者单位】： 河南科技大学管理学院;
【基金】：国家社会科学基金青年项目“面向专利数据的多重共现分析方法及其在技术创新网络中的应用研究”(编号:14CTQ018) 河南省高等学校哲学社会科学研究优秀学者资助项目(编号:2017-YXXZ-07)的成果
【分类号】：G353.1
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