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Visualizing and tracking the growth of competing paradigms: Two case studies

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Listed:
  • Chaomei Chen
  • Timothy Cribbin
  • Robert Macredie
  • Sonali Morar

Abstract

In this article we demonstrate the use of an integrative approach to visualizing and tracking the development of scientific paradigms. This approach is designed to reveal the long‐term process of competing scientific paradigms. We assume that a cluster of highly cited and cocited scientific publications in a cocitation network represents the core of a predominant scientific paradigm. The growth of a paradigm is depicted and animated through the rise of citation rates and the movement of its core cluster towards the center of the cocitation network. We study two cases of competing scientific paradigms in the real world: (1) the causes of mass extinctions, and (2) the connections between mad cow disease and a new variant of a brain disease in humans—vCJD. Various theoretical and practical issues concerning this approach are discussed.

Suggested Citation

  • Chaomei Chen & Timothy Cribbin & Robert Macredie & Sonali Morar, 2002. "Visualizing and tracking the growth of competing paradigms: Two case studies," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 53(8), pages 678-689.
  • Handle: RePEc:bla:jamist:v:53:y:2002:i:8:p:678-689
    DOI: 10.1002/asi.10075
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    Cited by:

    1. Yuetong Chen & Hao Wang & Baolong Zhang & Wei Zhang, 2022. "A method of measuring the article discriminative capacity and its distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3317-3341, June.
    2. Yoshiyuki Takeda & Yuya Kajikawa, 2009. "Optics: a bibliometric approach to detect emerging research domains and intellectual bases," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(3), pages 543-558, March.
    3. Francesco Paolo Appio & Fabrizio Cesaroni & Alberto Minin, 2014. "Visualizing the structure and bridges of the intellectual property management and strategy literature: a document co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 623-661, October.
    4. Qian, Yue & Liu, Yu & Sheng, Quan Z., 2020. "Understanding hierarchical structural evolution in a scientific discipline: A case study of artificial intelligence," Journal of Informetrics, Elsevier, vol. 14(3).
    5. Linqing Liu & Shiye Mei, 2016. "Visualizing the GVC research: a co-occurrence network based bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 953-977, November.
    6. Chaomei Chen & Diana Hicks, 2004. "Tracing knowledge diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(2), pages 199-211, February.
    7. Xinwei Su & Xi Li & Yanxin Kang, 2019. "A Bibliometric Analysis of Research on Intangible Cultural Heritage Using CiteSpace," SAGE Open, , vol. 9(2), pages 21582440198, April.
    8. Acedo, Francisco José & Casillas, José Carlos, 2005. "Current paradigms in the international management field: An author co-citation analysis," International Business Review, Elsevier, vol. 14(5), pages 619-639, October.
    9. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    10. Yoshiyuki Takeda & Yuya Kajikawa, 2010. "Tracking modularity in citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 783-792, June.
    11. Tsao, J.Y. & Boyack, K.W. & Coltrin, M.E. & Turnley, J.G. & Gauster, W.B., 2008. "Galileo's stream: A framework for understanding knowledge production," Research Policy, Elsevier, vol. 37(2), pages 330-352, March.
    12. Hui-Yun Sung & Hsi-Yin Yeh & Jin-Kwan Lin & Ssu-Han Chen, 2017. "A visualization tool of patent topic evolution using a growing cell structure neural network," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1267-1285, June.
    13. Francesco Paolo Appio & Antonella Martini & Silvia Massa & Stefania Testa, 2016. "Unveiling the intellectual origins of Social Media-based innovation: insights from a bibliometric approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 355-388, July.

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