Turning the Tables on Citation Analysis One More Time: Principles for Comparing Sets of Documents
Turning the Tables on Citation Analysis One More Time: Principles for Comparing Sets of Documents
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DOI：
10.1002/asi.21534
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发表时间：
2011-07-01
影响因子：
--
通讯作者：
Opthof, Tobias
中科院分区：
文献类型：
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作者：
Leydesdorff, Loet;Bornmann, Lutz;Opthof, Tobias
我们提交了新开发的引文影响指标，而不是基于引文的算术平均值，而是基于百分位数排名。引文分布通常是高度倾斜的，不应该进行算术平均。通过百分位排名，每篇论文的引用分数根据其在引用分布中的百分位进行评级。百分位排序法允许制定一个更抽象的指标计划，用于根据三个自由度组织和/或规划不同的影响指标：参考集的选择、评价标准和是否将出版物集定义为独立的选择。阿姆斯特丹大学学术医学中心的七位主要研究者（PI）的文献计量数据被用作示例性数据集。我们证明了所提出的族指标[R（6），R（100），R（6，k），R（100，k）]是对基于平均值的指标的改进，因为可以考虑论文引用分布的形状。
We submit newly developed citation impact indicators based not on arithmetic averages of citations but on percentile ranks. Citation distributions are-as a rule-highly skewed and should not be arithmetically averaged. With percentile ranks, the citation score of each paper is rated in terms of its percentile in the citation distribution. The percentile ranks approach allows for the formulation of a more abstract indicator scheme that can be used to organize and/or schematize different impact indicators according to three degrees of freedom: the selection of the reference sets, the evaluation criteria, and the choice of whether or not to define the publication sets as independent. Bibliometric data of seven principal investigators (PIs) of the Academic Medical Center of the University of Amsterdam are used as an exemplary dataset. We demonstrate that the proposed family indicators [R(6), R(100), R(6, k), R(100, k)] are an improvement on averages-based indicators because one can account for the shape of the distributions of citations over papers.