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Pandemics are catalysts of scientific novelty: Evidence from COVID‐19

Author

Listed:
  • Meijun Liu
  • Yi Bu
  • Chongyan Chen
  • Jian Xu
  • Daifeng Li
  • Yan Leng
  • Richard B. Freeman
  • Eric T. Meyer
  • Wonjin Yoon
  • Mujeen Sung
  • Minbyul Jeong
  • Jinhyuk Lee
  • Jaewoo Kang
  • Chao Min
  • Min Song
  • Yujia Zhai
  • Ying Ding

Abstract

Scientific novelty drives the efforts to invent new vaccines and solutions during the pandemic. First‐time collaboration and international collaboration are two pivotal channels to expand teams' search activities for a broader scope of resources required to address the global challenge, which might facilitate the generation of novel ideas. Our analysis of 98,981 coronavirus papers suggests that scientific novelty measured by the BioBERT model that is pretrained on 29 million PubMed articles, and first‐time collaboration increased after the outbreak of COVID‐19, and international collaboration witnessed a sudden decrease. During COVID‐19, papers with more first‐time collaboration were found to be more novel and international collaboration did not hamper novelty as it had done in the normal periods. The findings suggest the necessity of reaching out for distant resources and the importance of maintaining a collaborative scientific community beyond nationalism during a pandemic.

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  • Meijun Liu & Yi Bu & Chongyan Chen & Jian Xu & Daifeng Li & Yan Leng & Richard B. Freeman & Eric T. Meyer & Wonjin Yoon & Mujeen Sung & Minbyul Jeong & Jinhyuk Lee & Jaewoo Kang & Chao Min & Min Song , 2022. "Pandemics are catalysts of scientific novelty: Evidence from COVID‐19," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(8), pages 1065-1078, August.
    • Handle: RePEc:bla:jinfst:v:73:y:2022:i:8:p:1065-1078
    DOI: 10.1002/asi.24612
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    6. Meijun Liu & Sijie Yang & Yi Bu & Ning Zhang, 2023. "Female early-career scientists have conducted less interdisciplinary research in the past six decades: evidence from doctoral theses," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
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    9. Mengjia Wu & Yi Zhang & Mark Markley & Caitlin Cassidy & Nils Newman & Alan Porter, 2024. "COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7229-7259, November.

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