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Citation concept analysis (CCA): a new form of citation analysis revealing the usefulness of concepts for other researchers illustrated by exemplary case studies including classic books by Thomas S. Kuhn and Karl R. Popper

Author

Listed:
  • Lutz Bornmann

    (Administrative Headquarters of the Max Planck Society)

  • K. Brad Wray

    (Aarhus University)

  • Robin Haunschild

    (Max Planck Institute for Solid State Research)

Abstract

In recent years, the full text of papers are increasingly available electronically which opens up the possibility of quantitatively investigating citation contexts in more detail. In this study, we introduce a new form of citation analysis, which we call citation concept analysis (CCA). CCA is intended to reveal the cognitive impact certain concepts—published in a highly-cited landmark publication—have on the citing authors. It counts the number of times the concepts are mentioned (cited) in the citation context of citing publications. We demonstrate the method using three classical highly cited books: (1) The structure of scientific revolutions by Thomas S. Kuhn, (2) The logic of scientific discovery—Logik der Forschung: Zur Erkenntnistheorie der modernen Naturwissenschaft in German—, and (3) Conjectures and refutations: the growth of scientific knowledge by Karl R. Popper. It is not surprising—as our results show—that Kuhn’s “paradigm” concept seems to have had a significant impact. What is surprising is that our results indicate a much larger impact of the concept “paradigm” than Kuhn’s other concepts, e.g., “scientific revolution”. The paradigm concept accounts for about 40% of the concept-related citations to Kuhn’s work, and its impact is resilient across all disciplines and over time. With respect to Popper, “falsification” is the most used concept derived from his books. Falsification is the cornerstone of Popper’s critical rationalism.

Suggested Citation

  • Lutz Bornmann & K. Brad Wray & Robin Haunschild, 2020. "Citation concept analysis (CCA): a new form of citation analysis revealing the usefulness of concepts for other researchers illustrated by exemplary case studies including classic books by Thomas S. K," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 1051-1074, February.
    • Handle: RePEc:spr:scient:v:122:y:2020:i:2:d:10.1007_s11192-019-03326-2
    DOI: 10.1007/s11192-019-03326-2
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    References listed on IDEAS

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    1. Iman Tahamtan & Lutz Bornmann, 2019. "What do citation counts measure? An updated review of studies on citations in scientific documents published between 2006 and 2018," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1635-1684, December.
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    Cited by:

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    3. Jodi Schneider & Di Ye & Alison M. Hill & Ashley S. Whitehorn, 2020. "Continued post-retraction citation of a fraudulent clinical trial report, 11 years after it was retracted for falsifying data," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2877-2913, December.
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    6. Naif Radi Aljohani & Ayman Fayoumi & Saeed-Ul Hassan, 2021. "An in-text citation classification predictive model for a scholarly search system," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5509-5529, July.

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