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Using Hypertext Metrics to Measure Research Output Levels

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  • Paul De Bra

    (Eindhoven University of Technology)

Abstract

Two common ways to measure the "output" of a researcher (or research group) are to count numbers of publications and to count the citations (references to these publications in publications of others). These simple methods are flawed because they cannot easily take into account the differences in publication and citation habits in different scientific communities. An alternative approach is to view citations as hypertext links, and to use or adapt hypertext metrics to compare the scientific output of researchers, in comparison to that of others in areas with similar publication and citation patterns. We show how hypertext metrics, introduced by Botafogo, Rivlin and Shneiderman, can be modified in order to identify comparable research fields based on their publication and citation pattern. An author's performance can then be compared to that of others in research fields with a similar pattern.

Suggested Citation

  • Paul De Bra, 2000. "Using Hypertext Metrics to Measure Research Output Levels," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 227-236, February.
    • Handle: RePEc:spr:scient:v:47:y:2000:i:2:d:10.1023_a:1005682808896
    DOI: 10.1023/A:1005682808896
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    Cited by:

    1. Fang Yong & Ronald Rousseau, 2001. "Lattices in citation networks: An investigation into the structure of citation graphs," Scientometrics, Springer;Akadémiai Kiadó, vol. 50(2), pages 273-287, February.
    2. Leo Egghe & Ronald Rousseau, 2002. "Co-citation, bibliographic coupling and a characterization of lattice citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 55(3), pages 349-361, November.
    3. Liu, Yuxian & Rousseau, Ronald & Egghe, Leo, 2017. "Partial orders for zero-sum arrays with applications to network theory," Journal of Informetrics, Elsevier, vol. 11(1), pages 257-274.

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