Research topic displacement and the lack of interdisciplinarity: lessons from the scientific response to COVID-19

IF 3.5 3区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Scientometrics Pub Date : 2024-08-22 DOI:10.1007/s11192-024-05132-x
Eva Seidlmayer, Tetyana Melnychuk, Lukas Galke, Lisa Kühnel, Klaus Tochtermann, Carsten Schultz, Konrad U. Förstner
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Abstract

Based on a large-scale computational analysis of scholarly articles, this study investigates the dynamics of interdisciplinary research in the first year of the COVID-19 pandemic. Thereby, the study also analyses the reorientation effects away from other topics that receive less attention due to the high focus on the COVID-19 pandemic. The study aims to examine what can be learned from the (failing) interdisciplinarity of coronavirus research and its displacing effects for managing potential similar crises at the scientific level. To explore our research questions, we run several analyses by using the COVID-19++ dataset, which contains scholarly publications, preprints from the field of life sciences, and their referenced literature including publications from a broad scientific spectrum. Our results show the high impact and topic-wise adoption of research related to the COVID-19 crisis. Based on the similarity analysis of scientific topics, which is grounded on the concept embedding learning in the graph-structured bibliographic data, we measured the degree of interdisciplinarity of COVID-19 research in 2020. Our findings reveal a low degree of research interdisciplinarity. The publications’ reference analysis indicates the major role of clinical medicine, but also the growing importance of psychiatry and social sciences in COVID-19 research. A social network analysis shows that the authors’ high degree of centrality significantly increases her or his degree of interdisciplinarity.

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研究课题转移和缺乏跨学科性:从科学界对 COVID-19 的反应中汲取的教训
基于对学术文章的大规模计算分析,本研究调查了 COVID-19 大流行第一年的跨学科研究动态。因此,本研究还分析了由于高度关注 COVID-19 大流行而对其他关注度较低的主题产生的方向调整效应。本研究旨在探讨从冠状病毒研究的(失败的)跨学科性中可以学到什么,以及它在科学层面管理潜在的类似危机时产生的转移效应。为了探讨我们的研究问题,我们使用 COVID-19++ 数据集进行了多项分析,该数据集包含生命科学领域的学术出版物、预印本及其参考文献,其中包括来自广泛科学领域的出版物。我们的研究结果表明,与 COVID-19 危机相关的研究具有很高的影响力,并在不同主题上得到了广泛采用。基于图结构书目数据中概念嵌入学习的科学主题相似性分析,我们衡量了 2020 年 COVID-19 研究的跨学科程度。我们的研究结果表明,研究的跨学科程度较低。出版物参考文献分析表明,临床医学在 COVID-19 研究中发挥着主要作用,但精神病学和社会科学的重要性也在不断增加。社会网络分析显示,作者的中心度越高,其跨学科程度就越高。
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来源期刊
Scientometrics
Scientometrics 管理科学-计算机:跨学科应用
CiteScore
7.20
自引率
17.90%
发文量
351
审稿时长
1.5 months
期刊介绍: Scientometrics aims at publishing original studies, short communications, preliminary reports, review papers, letters to the editor and book reviews on scientometrics. The topics covered are results of research concerned with the quantitative features and characteristics of science. Emphasis is placed on investigations in which the development and mechanism of science are studied by means of (statistical) mathematical methods. The Journal also provides the reader with important up-to-date information about international meetings and events in scientometrics and related fields. Appropriate bibliographic compilations are published as a separate section. Due to its fully interdisciplinary character, Scientometrics is indispensable to research workers and research administrators throughout the world. It provides valuable assistance to librarians and documentalists in central scientific agencies, ministries, research institutes and laboratories. Scientometrics includes the Journal of Research Communication Studies. Consequently its aims and scope cover that of the latter, namely, to bring the results of research investigations together in one place, in such a form that they will be of use not only to the investigators themselves but also to the entrepreneurs and research workers who form the object of these studies.
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