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Number of references: a large-scale study of interval ratios
Scientometrics ( IF 3.9 ) Pub Date : 2020-11-04 , DOI: 10.1007/s11192-020-03764-3
Jeppe Nicolaisen , Tove Faber Frandsen

The paper presents a large-scale study (covering 26,998,764 items) of the development in the number of references over time (1996–2019) in three document types (articles; reviews; notes) from seven fields (Arts and Humanities; Social Sciences; Computer Science; Mathematics; Engineering; Medicine; Physics and Astronomy). Using interval ratios instead of average numbers, the paper makes it possible to follow the development, and to locate the main causes of growth in the number of references over time. The results show significant differences between fields and document types. The number of references in journal articles and reviews are growing in all fields (except for the reviews in Arts and Humanities that remain stable over time), but at different pace; The number of references in notes are growing in some fields (again at different pace) and are stable in others. The observed growth is primarily caused by a drop in short reference lists and a corresponding increase in a bit longer and medium size reference lists. Long and very long reference lists remain much more stable in shares over time, and does therefore not contribute much to the observed growth. The results underline the importance of normalizing citation data, and for taking citation inflation into account when conducting citation analyses expanding different fields, document types, and longer time-periods.

中文翻译:

参考文献数量:区间比的大规模研究

该论文对来自七个领域(艺术与人文科学;社会科学;计算机科学;数学;工程;医学;物理和天文学)。使用间隔比率而不是平均数,本文可以跟踪发展情况,并找出参考文献数量随时间增长的主要原因。结果显示字段和文档类型之间存在显着差异。所有领域的期刊文章和评论中的参考文献数量都在增长(除了艺术和人文领域的评论随着时间的推移保持稳定),但速度不同;笔记中的参考文献数量在某些领域(再次以不同的速度)增长,而在其他领域则稳定。观察到的增长主要是由于短参考列表的减少以及较长和中等大小的参考列表的相应增加造成的。随着时间的推移,很长和很长的参考列表在份额中保持更加稳定,因此对观察到的增长没有太大贡献。结果强调了标准化引文数据的重要性,以及在进行引文分析扩展不同领域、文档类型和更长的时间段时考虑引文膨胀的重要性。随着时间的推移,很长和很长的参考列表在份额中保持更加稳定,因此对观察到的增长没有太大贡献。结果强调了标准化引文数据的重要性,以及在进行引文分析扩展不同领域、文档类型和更长的时间段时考虑引文膨胀的重要性。随着时间的推移,很长和很长的参考列表在份额中保持更加稳定,因此对观察到的增长没有太大贡献。结果强调了标准化引文数据的重要性,以及在进行引文分析扩展不同领域、文档类型和更长的时间段时考虑引文膨胀的重要性。
更新日期:2020-11-04
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