Lando Tommaso, Bertoli-Barsotti Lucio
Department of Finance, VŠB Technical University of Ostrava, Ostrava, Czech Republic.
Dipartimento di Scienze aziendali, economiche e metodi quantitativi, University of Bergamo, Bergamo, Italy.
PLoS One. 2014 Dec 26;9(12):e115962. doi: 10.1371/journal.pone.0115962. eCollection 2014.
In order to improve the h-index in terms of its accuracy and sensitivity to the form of the citation distribution, we propose the new bibliometric index [symbol in text]. The basic idea is to define, for any author with a given number of citations, an "ideal" citation distribution which represents a benchmark in terms of number of papers and number of citations per publication, and to obtain an index which increases its value when the real citation distribution approaches its ideal form. The method is very general because the ideal distribution can be defined differently according to the main objective of the index. In this paper we propose to define it by a "squared-form" distribution: this is consistent with many popular bibliometric indices, which reach their maximum value when the distribution is basically a "square". This approach generally rewards the more regular and reliable researchers, and it seems to be especially suitable for dealing with common situations such as applications for academic positions. To show the advantages of the [symbol in text]-index some mathematical properties are proved and an application to real data is proposed.
为了提高h指数在准确性和对引文分布形式的敏感性方面的表现,我们提出了新的文献计量指标[文中符号]。基本思路是,对于任何拥有给定引文数量的作者,定义一种“理想”的引文分布,该分布在论文数量和每篇出版物的引文数量方面代表一个基准,并获得一个指标,当实际引文分布接近其理想形式时,该指标的值会增加。该方法非常通用,因为理想分布可以根据指标的主要目标进行不同的定义。在本文中,我们建议通过“平方形式”分布来定义它:这与许多流行的文献计量指标一致,当分布基本为“方形”时,这些指标达到最大值。这种方法通常会奖励更规范、更可靠的研究人员,并且似乎特别适合处理诸如学术职位申请等常见情况。为了展示[文中符号]指标的优势,我们证明了一些数学性质,并提出了对实际数据的应用。