跨学科研究的延迟引用影响

IF 3.4 2区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Informetrics Pub Date : 2023-11-30 DOI:10.1016/j.joi.2023.101468
Yang Zhang , Yang Wang , Haifeng Du , Shlomo Havlin
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引用次数: 0

摘要

跨学科研究日益推动创新,是未来突破的关键投入。然而,跨学科研究何时达到最高的引用影响仍不清楚。本文采用论文达到被引高峰的时间来量化被引动态,并考察其与论文跨学科性的关系。通过使用37年的大型出版物数据集,我们的研究结果表明,跨学科论文在单个论文水平和整体水平上都表现出显著的延迟引用影响,因为高度跨学科的论文需要更长的时间才能达到被引高峰和半被引。这种关系在不同的科学学科和时期几乎是普遍存在的。此外,我们研究了这种延迟影响背后的潜在力量,发现这种影响超出了马太效应(即富者愈富效应)。虽然团队规模和内容约定俗成与引文延迟有一定的关系,但不能完全解释这种影响。总体而言,我们的研究结果表明,政府、科研管理者和资助机构应该意识到跨学科科学的这一普遍特征,这可能具有广泛的政策含义。
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Delayed citation impact of interdisciplinary research

Interdisciplinary research increasingly fuels innovation, and is a key input for future breakthroughs. Yet the timing of when interdisciplinary research achieves its highest citation impact remains unclear. Here, we use the time of a paper to reach its citation peak to quantify citation dynamics, and examine its relationship with paper interdisciplinarity. Using large scale publication datasets spanning over 37 years, our results suggest that interdisciplinary papers show significant delayed citation impact both at the individual paper level and collectively, as it takes longer for highly interdisciplinary papers to reach their citation peak as well as their half citations. Such relationships are nearly universal across various scientific disciplines and time periods. Furthermore, we study the underlying forces behind this delayed impact, finding that the effect goes beyond the Matthew effect (i.e., the rich-get-richer effect). Although team size and content conventionality are partly related to the citation delay, they cannot fully explain this effect. Overall, our results suggest that governments, research administrators, and funding agencies should be aware of this general feature of interdisciplinary science, which may have broad policy implications.

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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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