通过跨学科引文的关键年份探索跨学科研究趋势

IF 3.5 2区管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Informetrics Pub Date : 2025-09-12 DOI:10.1016/j.joi.2025.101726

Guoyang Rong , Ying Chen , Feicheng Ma , Thorsten Koch

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引用次数: 0

摘要

本研究考察了近40年来跨学科研究的历史演变，重点探讨了其动态趋势、阶段和关键转折点。我们应用时间序列分析来确定跨学科引文（CYICs）的关键年份，并根据这些趋势将IDR分为三个不同的阶段：第一阶段（1981-2002），以零星和有限的跨学科活动为特征；第二阶段（2003-2016），以医学为主导的大规模IDR出现，克隆技术和医学技术取得重大突破；第三阶段（2017-2020），IDR成为广泛采用的研究范式。我们的研究结果表明，IDR主要集中在自然科学领域，医学一直处于前沿，并强调工程和环境学科的贡献日益增加，这是一种新趋势。这些见解增强了对IDR演变、其驱动因素以及跨学科焦点转移的理解。

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Exploring interdisciplinary research trends through critical years for interdisciplinary citation

This study examines the historical evolution of interdisciplinary research (IDR) over a 40-year period, focusing on its dynamic trends, phases, and key turning points. We apply time series analysis to identify critical years for interdisciplinary citations (CYICs) and categorizes IDR into three distinct phases based on these trends: Period I (1981–2002), marked by sporadic and limited interdisciplinary activity; Period II (2003–2016), characterized by the emergence of large-scale IDR led primarily by Medicine, with significant breakthroughs in cloning and medical technology; and Period III (2017–2020), where IDR became a widely adopted research paradigm. Our findings indicate that IDR has been predominantly concentrated within the Natural Sciences, with Medicine consistently at the forefront, and highlights increasing contributions from Engineering and Environmental disciplines as a new trend. These insights enhance the understanding of the evolution of IDR, its driving factors, and the shifts in the focus of interdisciplinary.

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来源期刊

Journal of Informetrics Social Sciences-Library and Information Sciences

CiteScore

6.40

自引率

16.20%

发文量

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.