COVID-19: a disruptive impact on the knowledge support of references

Yujie Zhang (), Hongzhen Li (), Jingyi Mao (), Guoxiu He (), Yunhan Yang (), Zhuoren Jiang () and Yufeng Duan ()
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Yujie Zhang: East China Normal University
Hongzhen Li: East China Normal University
Jingyi Mao: East China Normal University
Guoxiu He: East China Normal University
Yunhan Yang: The University of Hong Kong
Zhuoren Jiang: Zhejiang University
Yufeng Duan: East China Normal University

Scientometrics, 2023, vol. 128, issue 8, No 26, 4823 pages

Abstract: Abstract According to existing research, in the general scientific backdrop, individuals prefer to employ old and well-established knowledge to promote scientific advancement, resulting in the progress of science in a set direction. When the disruption event COVID-19 occurred, however, people’s demand for breakthrough research, such as vaccinations or treatments, became increasingly pressing. Under such circumstances, can the accumulated coronavirus-related knowledge still give solid support for COVID-19 research? The manner of utilizing and absorbing new knowledge in the citing publications is reflected in the reference analysis. To investigate this proposition, we employ reference analysis to conduct retrospectives on relevant scientific articles. We locate 309,517 related papers and their references in the CORD-19 data from 2000 to 2021. We analyze the knowledge support capacity of previous studies from three aspects: the quantity, timeliness, and textual support of references. Among them, textual support is divided into lexical, topic, and semantic support, which are respectively based on TF-IDF, LDA, and fine-tuned sentence-BERT. Our findings demonstrate that COVID-19 has caused unprecedented destruction of the original knowledge support pattern in the early stages of research (which is at odds with the knowledge support pattern in the general scientific background). The long-term accumulated and non-direct knowledge provides brief support for the COVID-19 investigation. Follow-up research will swiftly replace outdated information with new study findings. The appeal of the scientific community has moved from “return to the past” to “innovative alternatives”. We divide the process into three stages: rearrangement, iteration, and growth. The loss in knowledge support capacity following a disruptive event such as COVID-19 enhances the difficulty of research. However, it cannot be ignored that it has also considerably sped the pace of knowledge production.

Keywords: COVID-19; Reference support; Reference analysis; Science of science; Sentence-BERT (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11192-023-04764-9

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