文章摘要
徐爽,付怡,许丹,罗祥东.MeSH 主题词与关键短语在表现学科主题结构及发展演化上的比较研究[J].情报工程,2026,(3):019-034
MeSH 主题词与关键短语在表现学科主题结构及发展演化上的比较研究
A Comparative Study of Medical Subject Headings and Key Phrases in Expressing the Theme Structure and Development Evolution of Disciplines
  
DOI:
中文关键词: 共词分析;社会网络分析;MeSH 主题词;主题结构;主题演化
英文关键词: Co-word Analysis; Social Network Analysis; Medical Subject Headings (MeSH); Theme Structure; Theme Evolution
基金项目:辽宁省社会科学规划基金项目“语义关系视角下面向患者需求的健康管理知识组织与服务研究”(L21BTQ008)。
作者单位
徐爽 1. 中国医科大学图书馆 沈阳 110122; 
付怡 2. 中国医科大学健康管理学院 沈阳 110122 
许丹 1. 中国医科大学图书馆 沈阳 110122; 
罗祥东 1. 中国医科大学图书馆 沈阳 110122; 
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中文摘要:
      [目的/ 意义] 比较MeSH 主题词与从文献标题与摘要中抽取的关键短语在揭示领域主题关联结构和发展态势演 化方面的差异与优劣。以人格障碍领域文献为例,构建两种分析单元的共词网络、主题社区及其战略坐标图、主题演化图, 进行描述性对比分析,并邀请该领域专家对结果进行评估。[ 方法/ 过程] 通过定性与定量结合的方法揭示应用不同分 析单元的共词分析在反映研究主题关联结构、发展演化态势方面的差异与优劣。[ 结果/ 结论]MeSH 主题词网络在展现 主题间深层关联结构方面更具优势,而关键短语网络在识别具体研究热点社区、评估主题发展方向及描绘清晰演化路径 方面表现更优。本研究为共词分析时基于任务导向选择合适的分析单元提供了科学依据和实用指导。
英文摘要:
      [Objective/Significance] This study compared the differences between MeSH and key phrases extracted from literature titles and abstracts in revealing the theme structure and development evolution of disciplines. Taking literature in the field of personality disorders as an example, we constructed co-word networks, thematic communities and strategic coordinate maps for two analysis units. After conducting descriptive comparative analysis, experts in the field were invited to evaluate the results.[Methods/Processes] By combining qualitative and quantitative methods, this study aimed to reveal the differences of co-word analysis using different analysis units in reflecting the correlation structure and development trend of research topics. [Result/Conclusion] Research has found that the MeSH topic word network has a greater advantage in displaying the deep correlation structure between topics, while the key phrase network performs better in identifying specific research hotspot communities, evaluating topic development directions, and depicting clear evolutionary paths. This study provides scientific basis and practical guidance for selecting appropriate analysis units based on task orientation in co-word analysis.
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