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Knowledge diffusion through publications and citations: A case study using ESI‐fields as unit of diffusion

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  • Yuxian Liu
  • Ronald Rousseau

Abstract

Two forms of diffusion are studied: diffusion by publications, originating from the fact that a group publishes in different fields; and diffusion by citations, originating from the fact that the group's publications are cited in different fields. The first form of diffusion originates from an internal mechanism by which the group itself expands its own borders. The second form is partly driven by an external mechanism, in the sense that other fields use or become interested in the original group's expertise, and partly by the group's internal dynamism, in the sense that their articles, being published in more and more fields, have the potential to be applied in these other fields. In this contribution, we focus on basic counting measures as measures of diffusion. We introduce the notions of field diffusion breadth, defined as the number of for Essential Science Indicators (ESI) fields in which a set of articles is cited, and field diffusion intensity, defined as the number of citing articles in one particular ESI field. Combined effects of publications and citations can be measured by the Gini evenness measure. Our approach is illustrated by a study of mathematics at Tongji University (Shanghai, China).

Suggested Citation

  • Yuxian Liu & Ronald Rousseau, 2010. "Knowledge diffusion through publications and citations: A case study using ESI‐fields as unit of diffusion," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(2), pages 340-351, February.
  • Handle: RePEc:bla:jamist:v:61:y:2010:i:2:p:340-351
    DOI: 10.1002/asi.21248
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    Cited by:

    1. Stephen Carley & Alan L. Porter, 2012. "A forward diversity index," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 407-427, February.
    2. Rousseau, Ronald & Liu, Yuxian & Ye, Fred Y., 2012. "A preliminary investigation on diffusion through a layered system," Journal of Informetrics, Elsevier, vol. 6(2), pages 177-191.
    3. Yang, Jinqing & Liu, Zhifeng, 2022. "The effect of citation behaviour on knowledge diffusion and intellectual structure," Journal of Informetrics, Elsevier, vol. 16(1).
    4. Bornmann, Lutz & Marx, Werner, 2013. "The proposal of a broadening of perspective in evaluative bibliometrics by complementing the times cited with a cited reference analysis," Journal of Informetrics, Elsevier, vol. 7(1), pages 84-88.
    5. Wang, Jue & Zhang, Liwei, 2018. "Proximal advantage in knowledge diffusion: The time dimension," Journal of Informetrics, Elsevier, vol. 12(3), pages 858-867.
    6. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2021. "A bibliometric methodology to unveil territorial inequities in the scientific wealth to combat COVID-19," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6601-6624, August.
    7. Pan, Xuelian & Yan, Erjia & Cui, Ming & Hua, Weina, 2018. "Examining the usage, citation, and diffusion patterns of bibliometric mapping software: A comparative study of three tools," Journal of Informetrics, Elsevier, vol. 12(2), pages 481-493.
    8. Meijun Liu & Xiao Hu & Jiang Li, 2018. "Knowledge flow in China’s humanities and social sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(2), pages 607-626, March.
    9. Xia Gao & Jiancheng Guan, 2012. "Network model of knowledge diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 749-762, March.
    10. Saeed-Ul Hassan & Peter Haddawy, 2013. "Measuring international knowledge flows and scholarly impact of scientific research," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 163-179, January.
    11. Bei Zeng & Haihua Lyu & Zhenyue Zhao & Jiang Li, 2021. "Exploring the direction and diversity of interdisciplinary knowledge diffusion: A case study of professor Zeyuan Liu's scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6253-6272, July.
    12. Wang, Haiying & Moore, Jack Murdoch & Wang, Jun & Small, Michael, 2021. "The distinct roles of initial transmission and retransmission in the persistence of knowledge in complex networks," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    13. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Di Costa, Flavia, 2020. "Knowledge spillovers: Does the geographic proximity effect decay over time? A discipline-level analysis, accounting for cognitive proximity, with and without self-citations," Journal of Informetrics, Elsevier, vol. 14(4).
    14. Goldman, Alyssa W., 2014. "Conceptualizing the interdisciplinary diffusion and evolution of emerging fields: The case of systems biology," Journal of Informetrics, Elsevier, vol. 8(1), pages 43-58.
    15. Wang, Shiyun & Mao, Jin & Lu, Kun & Cao, Yujie & Li, Gang, 2021. "Understanding interdisciplinary knowledge integration through citance analysis: A case study on eHealth," Journal of Informetrics, Elsevier, vol. 15(4).
    16. Hu, Xiaojun & Rousseau, Ronald, 2018. "A new approach to explore the knowledge transition path in the evolution of science & technology: From the biology of restriction enzymes to their application in biotechnology," Journal of Informetrics, Elsevier, vol. 12(3), pages 842-857.
    17. Saeed-Ul Hassan & Peter Haddawy, 2015. "Analyzing knowledge flows of scientific literature through semantic links: a case study in the field of energy," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 33-46, April.
    18. Chen, Lixin, 2017. "Do patent citations indicate knowledge linkage? The evidence from text similarities between patents and their citations," Journal of Informetrics, Elsevier, vol. 11(1), pages 63-79.
    19. Fernández, Ana María & Ferrándiz, Esther & Medina, Jennifer, 2022. "The diffusion of energy technologies. Evidence from renewable, fossil, and nuclear energy patents," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    20. Xiaojun Hu & Ronald Rousseau & Jin Chen, 2012. "Structural indicators in citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 451-460, May.
    21. Xuan Liu & Shan Jiang & Hsinchun Chen & Catherine A. Larson & Mihail C. Roco, 2015. "Modeling knowledge diffusion in scientific innovation networks: an institutional comparison between China and US with illustration for nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1953-1984, December.
    22. Jiancheng Guan & Wenjia Zhu, 2014. "How knowledge diffuses across countries: a case study in the field of management," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 2129-2144, March.
    23. Rousseau, Ronald & Hu, Xiaojun, 2013. "Two time series, their meaning and some applications," Journal of Informetrics, Elsevier, vol. 7(3), pages 603-610.
    24. Liu, Yuxian & Rousseau, Ronald & Guns, Raf, 2013. "A layered framework to study collaboration as a form of knowledge sharing and diffusion," Journal of Informetrics, Elsevier, vol. 7(3), pages 651-664.

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