目的/意义 了解医学院校高被引论文在不同数据库中多源评价指标相关性,为文献资源发现、利用、评估提供参考.方法/过程 以2013-2023 年首都医科大学高被引论文为研究对象,分析其在H1 Connect、Di-mensions、ESI、Web of Science、InCites、SciVal数据库中的38 个评价指标,对代表性指标,专利、政策引用指标,浏览使用指标,相对指标,期刊指标,被引频次,Altmetric指标分别进行相关性分析.结果/结论 各组相似指标具有相对较高相关性,个别指标如加权星级和微博提及数与大多数不同平台指标没有显著相关性.
Study on Correlation of Evaluation Indexes of Multi-source Data for Highly Cited Papers from Medical Universities
Purpose/Significance To understand the correlation of multi-source evaluation indicators for highly cited papers in medi-cal universities in different databases,and to provide references for the discovery,utilization and evaluation of literature resources.Meth-od/Process The paper takes the highly cited papers of Capital Medical University from 2013 to 2023 as the research object,analyzes 38 e-valuation indexes in H1 Connect,Dimensions,ESI,Web of Science,InCites and SciVal,and makes correlation analysis from representative indicators,patent and policy citation indicators,browse and use indicators,relative indicators,journal indicators,cited frequency and Alt-metric indicators.Result/Conclusion It is found that the similar indicators in each group have relatively high correlation,individual indicators such as peer-reviewed weighted sum of stars and Weibo mentions have no significant correlation with most different platform indicators.
highly cited paperspaper evaluation indexcorrelation analysismulti-source data
万方数据
维普
