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[目的/意义]利用社会网络分析(SNA),基于学科内容,探讨科研人员隐性合作研究范式,既为具体学科领域内的学者提供研究热点、领军人物等数据,又推动了情报学分析方法在学科领域的应用。[方法/过程]以Pub Med中2型糖尿病科研文献的第一作者而非全体作者为研究对象,运用SNA方法进行作者与研究方向间关联关系、关联关系定量测度和结构呈现。[结果/结论]基于学科内容,以作者—关键词关联分析、作者—关键词耦合分析可以更加全面、深入、精准地挖掘科研人员的合作关系协作。以第一作者为研究对象可更准确揭示领域的领军人物、核心及次核心桥梁作者、主要及前沿研究热点等。[局限]文章仅选取了高频关键词,未触及次高频以及低频关键词。
[Purpose / Significance] Using social network analysis (SNA), based on the content of the subject, explore the research paradigm of tacit cooperation between researchers, which not only provides the research scholars and leaders with data in specific subject areas, but also promotes the method of intelligence analysis In the field of application. [Methods / Procedures] The first author of the published research articles on type 2 diabetes in PubMed, but not the entire author, was used as the research object. The SNA method was used to study the relationship between the author and the research direction, the quantitative relationship between the authors and the structure. [Result / Conclusion] Based on the content of the subject, the author-keyword correlation analysis and author-keyword coupling analysis can be used to explore the cooperation and collaborations among researchers in a more comprehensive, in-depth and accurate manner. With the first author as the research object, we can more accurately reveal the leaders, core and sub-core authors, and major and frontier research hot spots in the field. [Limitations] The article selects only the high-frequency keywords, sub-high frequency and low-frequency keywords are not touched.