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Measuring knowledge flow in the interdisciplinary field of biosecurity: full counting method or fractional counting method?

Author

Listed:
  • Xi Wang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Dongqiao Li

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Xiwen Liu

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Zhiqiang Wang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

Abstract

In the context of widespread concern about interdisciplinary phenomena, knowledge flows provide a dynamic and reliable perspective for understanding complex interdisciplinary phenomena. By reviewing the relevant literatures, it is found that existing studies usually calculate knowledge flows based on the full counting method. However, it remains uncertain which of these two methods, the full counting method or the fractional counting method, can measure the knowledge flow of interdisciplinary research more effective. Therefore, this study takes the field of biosecurity research as an example, designs the SP index based on the fractional counting method, and compares the full counting method with the fractional counting method in terms of knowledge flow, knowledge flow proportion, knowledge flow growth rate, etc. The results illustrate that, compared to the full counting method, the fractional counting method can provide a more fine-grained perspective, which reduces the data bias caused by a large number of citations from the same discipline in one article. Furthermore, this study divides the contribution of different disciplines into four types through SP index: Core Disciplines, Emerging Disciplines, Alternative Disciplines and Marginal Disciplines. Then, from the perspective of knowledge flow, in the same period of time, it is proposed that Core Disciplines contribute the most knowledge to the solution of biosecurity issues, while Marginal Disciplines contribute the least, among these four roles. Different researchers can select disciplines with different roles for interdisciplinary research according to their own needs. The research results also show that the roles of disciplines may change at different time stages. And the division of disciplinary roles further verifies that the fractional counting method can more accurately describe the flow of interdisciplinary knowledge. This study provides a reference for promoting further collaboration across disciplines and assisting stakeholders to identify appropriate disciplines for collaboration.

Suggested Citation

  • Xi Wang & Dongqiao Li & Xiwen Liu & Zhiqiang Wang, 2025. "Measuring knowledge flow in the interdisciplinary field of biosecurity: full counting method or fractional counting method?," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(2), pages 1101-1128, February.
  • Handle: RePEc:spr:scient:v:130:y:2025:i:2:d:10.1007_s11192-025-05249-7
    DOI: 10.1007/s11192-025-05249-7
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    References listed on IDEAS

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    1. Yoonjung An & Mintak Han & Yongtae Park, 2017. "Identifying dynamic knowledge flow patterns of business method patents with a hidden Markov model," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 783-802, November.
    2. Alexis-Michel Mugabushaka & Anthi Kyriakou & Theo Papazoglou, 2016. "Bibliometric indicators of interdisciplinarity: the potential of the Leinster–Cobbold diversity indices to study disciplinary diversity," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 593-607, May.
    3. Saeed-Ul Hassan & Iqra Safder & Anam Akram & Faisal Kamiran, 2018. "A novel machine-learning approach to measuring scientific knowledge flows using citation context analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 973-996, August.
    4. Lin Zhang & Ronald Rousseau & Wolfgang Glänzel, 2016. "Diversity of references as an indicator of the interdisciplinarity of journals: Taking similarity between subject fields into account," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(5), pages 1257-1265, May.
    5. George R. Heath & Ekaterina Kots & Janice L. Robertson & Shifra Lansky & George Khelashvili & Harel Weinstein & Simon Scheuring, 2021. "Localization atomic force microscopy," Nature, Nature, vol. 594(7863), pages 385-390, June.
    6. Henry Small, 2010. "Maps of science as interdisciplinary discourse: co-citation contexts and the role of analogy," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 835-849, June.
    7. Sivertsen, Gunnar & Rousseau, Ronald & Zhang, Lin, 2019. "Measuring scientific contributions with modified fractional counting," Journal of Informetrics, Elsevier, vol. 13(2), pages 679-694.
    8. Lu Huang & Yijie Cai & Erdong Zhao & Shengting Zhang & Yue Shu & Jiao Fan, 2022. "Measuring the interdisciplinarity of Information and Library Science interactions using citation analysis and semantic analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6733-6761, November.
    9. Guijie Zhang & Luning Liu & Fangfang Wei, 2019. "Key nodes mining in the inventor–author knowledge diffusion network," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 721-735, March.
    10. Loet Leydesdorff, 2018. "Diversity and interdisciplinarity: how can one distinguish and recombine disparity, variety, and balance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 2113-2121, September.
    11. Ma, Xiaowei & Jiao, Hong & Zhao, Yang & Huang, Shan & Yang, Bo, 2024. "Does open data have the potential to improve the response of science to public health emergencies?," Journal of Informetrics, Elsevier, vol. 18(2).
    12. Shiji Chen & Yanan Guo & Alvin Shijie Ding & Yanhui Song, 2024. "Is interdisciplinarity more likely to produce novel or disruptive research?," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(5), pages 2615-2632, May.
    13. Marianne Gauffriau & Peder Olesen Larsen, 2005. "Counting methods are decisive for rankings based on publication and citation studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(1), pages 85-93, July.
    14. Waltman, Ludo & van Eck, Nees Jan, 2015. "Field-normalized citation impact indicators and the choice of an appropriate counting method," Journal of Informetrics, Elsevier, vol. 9(4), pages 872-894.
    15. Mao, Jin & Liang, Zhentao & Cao, Yujie & Li, Gang, 2020. "Quantifying cross-disciplinary knowledge flow from the perspective of content: Introducing an approach based on knowledge memes," Journal of Informetrics, Elsevier, vol. 14(4).
    16. Chang, Ching-Wen & Yamanaka, Takayuki & Kano, Shingo, 2019. "An enforced loop-out knowledge flow facilitates industry competition: Learning from the pharmaceutical and genetically modified seed industries," Technovation, Elsevier, vol. 79(C), pages 11-24.
    17. Xia Cao & Chuanyun Li & Jinqiu Li & Yunchang Li, 2022. "Modeling and simulation of knowledge creation and diffusion in an industry-university-research cooperative innovation network: a case study of China’s new energy vehicles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3935-3957, July.
    18. Lyu, Haihua & Bu, Yi & Zhao, Zhenyue & Zhang, Jiarong & Li, Jiang, 2022. "Citation bias in measuring knowledge flow: Evidence from the web of science at the discipline level," Journal of Informetrics, Elsevier, vol. 16(4).
    19. Thed van Leeuwen & Robert Tijssen, 2000. "Interdisciplinary dynamics of modern science: analysis of cross-disciplinary citation flows," Research Evaluation, Oxford University Press, vol. 9(3), pages 183-187, December.
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