Rank analysis of most cited publications, a new approach for research assessments

IF 3.4 2区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Informetrics Pub Date : 2024-02-01 DOI:10.1016/j.joi.2024.101503
Alonso Rodríguez-Navarro , Ricardo Brito
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引用次数: 0

Abstract

Citation metrics are the best tools for research assessments. However, current metrics may be misleading in research systems that pursue simultaneously different goals, such as to push the boundaries of knowledge or incremental innovations, because their publications have different citation distributions. We estimate the contribution to the progress of knowledge by studying only a limited number of the most cited papers, which are dominated by publications pursuing this progress. To field-normalize the metrics, we substitute the number of citations by the rank position of papers from one country in the global list of papers. Using synthetic series of lognormally distributed numbers, simulating citations, we developed the Rk-index, which is calculated from the global ranks of the 10 highest numbers in each series, and demonstrate its equivalence to the number of papers in top percentiles, Ptop 0.1 % and Ptop 0.01 %. In real cases, the Rk-index is simple and easy to calculate, and evaluates the contribution to the progress of knowledge better than less stringent metrics. Although further research is needed, rank analysis of the most cited papers is a promising approach for research evaluation. It is also demonstrated that, for this purpose, domestic and collaborative papers should be studied independently.

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对被引用次数最多的出版物进行排名分析,这是一种新的研究评估方法
引用指标是研究评估的最佳工具。然而,在同时追求不同目标(如推动知识进步或渐进式创新)的研究系统中,当前的衡量标准可能会产生误导,因为它们的出版物具有不同的引用分布。我们只研究数量有限的被引用次数最多的论文,来估算这些论文对知识进步的贡献,因为这些论文主要是追求知识进步的论文。为了使度量指标现场正态化,我们用一个国家的论文在全球论文列表中的排名位置来代替引用次数。我们使用对数正态分布数字的合成序列来模拟引文,开发出了 Rk 指数,该指数由每个序列中最高的 10 个数字的全球排名计算得出,并证明了它等同于最高百分位数、Ptop 0.1 % 和 Ptop 0.01 % 的论文数量。在实际情况中,Rk-指数简单易算,与不太严格的指标相比,它能更好地评估对知识进步的贡献。尽管还需要进一步研究,但对被引用次数最多的论文进行排名分析是一种很有前途的研究评估方法。研究还表明,为此目的,应独立研究国内论文和合作论文。
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来源期刊
Journal of Informetrics
Journal of Informetrics Social Sciences-Library and Information Sciences
CiteScore
6.40
自引率
16.20%
发文量
95
期刊介绍: Journal of Informetrics (JOI) publishes rigorous high-quality research on quantitative aspects of information science. The main focus of the journal is on topics in bibliometrics, scientometrics, webometrics, patentometrics, altmetrics and research evaluation. Contributions studying informetric problems using methods from other quantitative fields, such as mathematics, statistics, computer science, economics and econometrics, and network science, are especially encouraged. JOI publishes both theoretical and empirical work. In general, case studies, for instance a bibliometric analysis focusing on a specific research field or a specific country, are not considered suitable for publication in JOI, unless they contain innovative methodological elements.
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