Scopus排名前1000的期刊中不同的CiteScore集群和百分位数

IF 1.6 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE
H. Okagbue, E. Akhmetshin, J. A. Teixeira da Silva
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引用次数: 1

摘要

Scopus/Elsevier的开放期刊指标CiteScore是Clarivate Analytics影响因子的一个有吸引力的替代方案。到2020年中期,用于计算CiteScore的公式发生了变化,反映了四年的数据窗口,而不是之前的三年数据集。从Scopus中推断出排名前1000的期刊的CiteScore数据,我们想了解CiteScore随时间的变化趋势。我们发现,从2015年到2019年,CiteScore平均每年都在持续增长,从13.877分增长到16.536分。从广义上讲,这反映了随着时间的推移,每份出版物被引用的次数越来越多,因此被引用率不断上升。学者们不应错误地将这种增长误认为是质量水平的提高。此外,百分位k-mean聚类和CiteScore聚类结果显示,排名前1000位的期刊存在三个不同的聚类,这些聚类由于具有明显的相似性(相似的平均值)而聚集在一起。这种模式可以帮助研究人员研究CiteScore的分布模式和百分位数如何随时间变化,并监测CiteScore方法多年来的演变情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distinct clusters of CiteScore and percentiles in top 1000 journals in Scopus
CiteScore, Scopus/Elsevier’s open journal metric, is an attractive alternativeto Clarivate Analytics’ impactfactor. Inmid-2020, theequation used to calculate the CiteScore changed, reflecting a four-year window of data versus a previous three-year data set. Extrapolating CiteScore data from Scopus for the top 1000 ranked journals, we wanted to appreciate how CiteScore trended over time. We found that, on average, CiteScore increased consistently each year between 2015 and 2019, from 13.877 to 16.536. Broadly, this reflects a greater number of citations per publication over time, so a constant rise in citation rate. Academics should not erroneously mistake this rise as a higher level of quality. In addition, k-mean clustering of the percentile and CiteScore showed the existence of three distinct clusters for the top 1000 ranked journals, which aggregated together due to their distinct similarities (similar mean). This pattern may assist researchers to study how the pattern of the distribution of CiteScore and percentile changes over time, and monitor how the CiteScore methodology has evolved over the years.
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来源期刊
COLLNET Journal of Scientometrics and Information Management
COLLNET Journal of Scientometrics and Information Management INFORMATION SCIENCE & LIBRARY SCIENCE-
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