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Appropriate Similarity Measures for Author Cocitation Analysis

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  • van Eck, N.J.P.
  • Waltman, L.

Abstract

We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.

Suggested Citation

  • van Eck, N.J.P. & Waltman, L., 2007. "Appropriate Similarity Measures for Author Cocitation Analysis," ERIM Report Series Research in Management ERS-2007-091-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:10889
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    References listed on IDEAS

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    1. Ludo Waltman & Nees Jan van Eck, 2007. "Some comments on the question whether co‐occurrence data should be normalized," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(11), pages 1701-1703, September.
    2. Per Ahlgren & Bo Jarneving & Ronald Rousseau, 2003. "Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(6), pages 550-560, April.
    3. Howard D. White, 2003. "Pathfinder networks and author cocitation analysis: A remapping of paradigmatic information scientists," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(5), pages 423-434, March.
    4. Jesper W. Schneider & Pia Borlund, 2007. "Matrix comparison, Part 1: Motivation and important issues for measuring the resemblance between proximity measures or ordination results," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(11), pages 1586-1595, September.
    5. Loet Leydesdorff & Liwen Vaughan, 2006. "Co‐occurrence matrices and their applications in information science: Extending ACA to the Web environment," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(12), pages 1616-1628, October.
    6. Katherine W. McCain, 1990. "Mapping authors in intellectual space: A technical overview," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 433-443, September.
    7. Waltman, L. & van Eck, N.J.P., 2007. "Some Comments on the Question Whether Co-occurrence Data Should Be Normalized," ERIM Report Series Research in Management ERS-2007-017-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
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    Cited by:

    1. Florian Noseleit, 2013. "Entrepreneurship, structural change, and economic growth," Journal of Evolutionary Economics, Springer, vol. 23(4), pages 735-766, September.

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    More about this item

    Keywords

    Pearson correlation; author cocitation analysis; cosine; information science; similarity measure;
    All these keywords.

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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