| 基于共词分析法的学科主题演化研究进展与分析 |
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| 引用本文： | 唐果媛,张薇.基于共词分析法的学科主题演化研究进展与分析[J].图书情报工作,2015,59(5):128-136. |
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| 作者姓名： | 唐果媛 张薇 |
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| 作者单位： | 1. 中国科学院文献情报中心 北京 100190;
2. 中国科学院大学 北京 100049 |
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| 摘 要： | 目的/意义]分析学科主题演化趋势,对科研人员研究学科知识、决策层规划学科布局都有重要意义.相比于词频分析法和共引分析法,共词分析法的优势是能深入文献内部,从微观角度揭示学科主题演化规律.分析中国国内基于共词分析法的学科主题演化研究现状,以期为相关研究人员提供参考和借鉴.方法/过程]采用人工判读法提炼出基于共词分析法的学科主题演化研究分析流程的5个步骤,并对每个步骤中研究人员使用的策略、分析手段和工具进行归纳总结.结果/结论]数据集的来源数据库主要有综合类、专门类和引文类等3种,检索策略有基于词、基于期刊和复合检索策略等3种;共词分析对象来源主要为作者关键词,关键词选取主要基于关键词词频、关键词共现词频和前两者相结合3个角度;构建共词矩阵时使用得最多的归一化系数为ochiai系数;最常用的主题演化分析手段为聚类分析和社会网络分析图谱;使用得最频繁的工具为SPSS软件.
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| 关 键 词： | 学科主题演化 共词分析法 主题演化阶段 检索策略 |
| 收稿时间： | 2015-01-07 |
Development and Analysis of Subject Theme Evolution Based on Co-word Analysis Method |
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| Tang Guoyuan,Zhang Wei.Development and Analysis of Subject Theme Evolution Based on Co-word Analysis Method[J].Library and Information Service,2015,59(5):128-136. |
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| Authors: | Tang Guoyuan Zhang Wei |
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| Institution: | 1. National Science Library, Chinese Academy of Sciences, Beijing 100190;
2. University of Chinese Academy of Sciences, Beijing 100049 |
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| Abstract: | Purpose/significance] It is significant to analyze the trend of subject theme evolution for researchers researching subject knowledge and policy makers planning subject layout. Compared to the word frequency analysis method and co-citation analysis method, co-word analysis method has the advantage of being able to deep inside the literatures, and revealing the rules of subject theme evolution. This paper studies the development of subject theme evolution based on co-word analysis method at home, so as to provide reference for the related researchers.Method/process] This paper uses manual interpretation method to extract five steps of research process of subject theme evolution based on co-word analysis. Furthermore, it summarizes the strategies, analysis methods or tools of the researchers using in each step. Result/conclusion] There are three kinds of main source databases of data sets: comprehensive database, special database, and citation database. There are three kinds of retrieval strategies: based on the words, based on the journals and composite retrieval strategy. The main source of co-word analysis object is author keyword. There are three kinds of main perspectives: based on keywords frequency, based on keywords co-occurrence frequency, and combination the previous two kinds. The Ochiai coefficient is used most widely of normalized coefficients when the co-word matrix is built. Clustering analysis and social network analysis map are used most widely of subject theme evolution analysis methods. SPSS software is used the most frequently. |
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| Keywords: | subject theme evolution co-word analysis theme evolutionary stage search strategy |
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