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

被引:1
作者
Seidlmayer, Eva [1 ]
Melnychuk, Tetyana [3 ]
Galke, Lukas [4 ,5 ,6 ]
Kuehnel, Lisa [1 ]
Tochtermann, Klaus [5 ]
Schultz, Carsten [3 ]
Foerstner, Konrad U. [1 ,2 ]
机构
[1] ZB MED Informat Ctr Life Sci, Data Sci & Serv, Gleueler Str 60, D-50931 Cologne, Germany
[2] TH Koln Univ Appl Sci, Inst Informat Wissensch, Claudiusstr 1, D-50678 Cologne, Germany
[3] Univ Kiel, Kiel Inst Responsible Innovat, Dept Technol Management, Westring 425, D-24118 Kiel, Germany
[4] Max Planck Inst Psycholinguist, Wundtlaan 1, NL-6525 XD Nijmegen, Netherlands
[5] ZBW Leibniz Informat Ctr Econ, Dusternbrooker Weg 120, D-24105 Kiel, Germany
[6] Univ Southern Denmark, Dept Math & Comp Sci, Campusvej 55, DK-5230 Odense, Denmark
关键词
COVID-19; Bibliometrics; Interdisciplinarity; Research dynamics; Network analysis; Machine learning; IMPACT; UNCERTAINTY; MANAGEMENT; SEARCH;
D O I
10.1007/s11192-024-05132-x
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:5141 / 5179
页数:39
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