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如何对期刊进行排名。

How to Rank Journals.

作者信息

Bradshaw Corey J A, Brook Barry W

机构信息

School of Biological Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia.

School of Biological Sciences, Private Bag 55, University of Tasmania, Hobart 7001, Australia.

出版信息

PLoS One. 2016 Mar 1;11(3):e0149852. doi: 10.1371/journal.pone.0149852. eCollection 2016.

Abstract

There are now many methods available to assess the relative citation performance of peer-reviewed journals. Regardless of their individual faults and advantages, citation-based metrics are used by researchers to maximize the citation potential of their articles, and by employers to rank academic track records. The absolute value of any particular index is arguably meaningless unless compared to other journals, and different metrics result in divergent rankings. To provide a simple yet more objective way to rank journals within and among disciplines, we developed a κ-resampled composite journal rank incorporating five popular citation indices: Impact Factor, Immediacy Index, Source-Normalized Impact Per Paper, SCImago Journal Rank and Google 5-year h-index; this approach provides an index of relative rank uncertainty. We applied the approach to six sample sets of scientific journals from Ecology (n = 100 journals), Medicine (n = 100), Multidisciplinary (n = 50); Ecology + Multidisciplinary (n = 25), Obstetrics & Gynaecology (n = 25) and Marine Biology & Fisheries (n = 25). We then cross-compared the κ-resampled ranking for the Ecology + Multidisciplinary journal set to the results of a survey of 188 publishing ecologists who were asked to rank the same journals, and found a 0.68-0.84 Spearman's ρ correlation between the two rankings datasets. Our composite index approach therefore approximates relative journal reputation, at least for that discipline. Agglomerative and divisive clustering and multi-dimensional scaling techniques applied to the Ecology + Multidisciplinary journal set identified specific clusters of similarly ranked journals, with only Nature & Science separating out from the others. When comparing a selection of journals within or among disciplines, we recommend collecting multiple citation-based metrics for a sample of relevant and realistic journals to calculate the composite rankings and their relative uncertainty windows.

摘要

现在有许多方法可用于评估同行评审期刊的相对被引表现。尽管基于引用的指标各有优缺点,但研究人员用其来最大化文章的被引潜力,雇主则用其来对学术记录进行排名。任何特定指标的绝对值,除非与其他期刊相比较,否则可能毫无意义,而且不同的指标会导致不同的排名结果。为了提供一种简单且更客观的方法来对学科内和学科间的期刊进行排名,我们开发了一种κ重采样综合期刊排名,纳入了五个常用的引用指标:影响因子、即时指数、每篇论文的来源标准化影响、SCImago期刊排名和谷歌5年h指数;这种方法提供了一个相对排名不确定性的指标。我们将该方法应用于来自生态学(n = 100种期刊)、医学(n = 100)、多学科(n = 50);生态学 + 多学科(n = 25)、妇产科学(n = 25)和海洋生物学与渔业(n = 25)的六个科学期刊样本集。然后,我们将生态学 + 多学科期刊集的κ重采样排名与一项针对188位发表过论文的生态学家的调查结果进行交叉比较,这些生态学家被要求对相同的期刊进行排名,结果发现两个排名数据集之间的斯皮尔曼相关系数ρ为0.68 - 0.84。因此,我们的综合指数方法至少在该学科内近似于期刊的相对声誉。应用于生态学 + 多学科期刊集的凝聚式和分裂式聚类以及多维缩放技术,识别出了排名相近的期刊的特定聚类,只有《自然》和《科学》与其他期刊区分开来。在比较学科内或学科间的一系列期刊时,我们建议收集多个基于引用的指标,针对一组相关且现实的期刊样本,以计算综合排名及其相对不确定性区间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/12eb/4773013/478424ae52ff/pone.0149852.g001.jpg

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