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Critical thresholds in co‐citation graphs

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  • W. M. Shaw

Abstract

Using the Random Graph Hypothesis, the statistical validity of co‐citation graphs has been investigated as a function of co‐citation strength for a given value of citation frequency. The results show that for both high and low values of co‐citation strength the partition of cited documents produced by the co‐citation relationship may be statistically invalid. Critical thresholds can be identified that define the limits of statistical validity. Within these limits, there is a narrow region of statistical validity where the associated structures are not an artifact of the clustering procedure and can be interpreted. It is concluded that the choice of citation and co‐citation thresholds can be influenced by formal considerations which insure statistically meaningful partitions rather than arbitrary decisions which can produce meaningless interpretations. Experimental and theoretical implications for the co‐citation graph and other bibliometric structures are discussed.

Suggested Citation

  • W. M. Shaw, 1985. "Critical thresholds in co‐citation graphs," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 36(1), pages 38-43, January.
    • Handle: RePEc:bla:jamest:v:36:y:1985:i:1:p:38-43
    DOI: 10.1002/asi.4630360104
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    Cited by:

    1. Dirk Tunger & Marc Eulerich, 2018. "Bibliometric analysis of corporate governance research in German-speaking countries: applying bibliometrics to business research using a custom-made database," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 2041-2059, December.
    2. Myriam Ertz & Sébastien Leblanc-Proulx, 2019. "Review of a proposed methodology for bibliometric and visualization analyses for organizations: application to the collaboration economy," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(2), pages 84-93, June.
    3. Pislyakov, Vladimir, 2022. "On some properties of medians, percentiles, baselines, and thresholds in empirical bibliometric analysis," Journal of Informetrics, Elsevier, vol. 16(4).

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