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A Principal Component Analysis of 39 Scientific Impact Measures

Author

Listed:
  • Johan Bollen
  • Herbert Van de Sompel
  • Aric Hagberg
  • Ryan Chute

Abstract

Background: The impact of scientific publications has traditionally been expressed in terms of citation counts. However, scientific activity has moved online over the past decade. To better capture scientific impact in the digital era, a variety of new impact measures has been proposed on the basis of social network analysis and usage log data. Here we investigate how these new measures relate to each other, and how accurately and completely they express scientific impact. Methodology: We performed a principal component analysis of the rankings produced by 39 existing and proposed measures of scholarly impact that were calculated on the basis of both citation and usage log data. Conclusions: Our results indicate that the notion of scientific impact is a multi-dimensional construct that can not be adequately measured by any single indicator, although some measures are more suitable than others. The commonly used citation Impact Factor is not positioned at the core of this construct, but at its periphery, and should thus be used with caution.

Suggested Citation

  • Johan Bollen & Herbert Van de Sompel & Aric Hagberg & Ryan Chute, 2009. "A Principal Component Analysis of 39 Scientific Impact Measures," PLOS ONE, Public Library of Science, vol. 4(6), pages 1-11, June.
  • Handle: RePEc:plo:pone00:0006022
    DOI: 10.1371/journal.pone.0006022
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    References listed on IDEAS

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    1. Johan Bollen & Herbert Van de Sompel & Aric Hagberg & Luis Bettencourt & Ryan Chute & Marko A Rodriguez & Lyudmila Balakireva, 2009. "Clickstream Data Yields High-Resolution Maps of Science," PLOS ONE, Public Library of Science, vol. 4(3), pages 1-11, March.
    2. Johan Bollen & Herbert Van de Sompel, 2008. "Usage impact factor: The effects of sample characteristics on usage‐based impact metrics," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(1), pages 136-149, January.
    3. Chen, P. & Xie, H. & Maslov, S. & Redner, S., 2007. "Finding scientific gems with Google’s PageRank algorithm," Journal of Informetrics, Elsevier, vol. 1(1), pages 8-15.
    4. Ronald Rousseau, 2005. "Median and percentile impact factors: A set of new indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 63(3), pages 431-441, June.
    5. Tim Brody & Stevan Harnad & Leslie Carr, 2006. "Earlier Web usage statistics as predictors of later citation impact," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(8), pages 1060-1072, June.
    6. Maria Bordons & M. T. Fernández & Isabel Gómez, 2002. "Advantages and limitations in the use of impact factor measures for the assessment of research performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 53(2), pages 195-206, February.
    7. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    8. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    9. Stephen P. Harter & Thomas E. Nisonger, 1997. "ISI's impact factor as misnomer: A proposed new measure to assess journal impact," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 48(12), pages 1146-1148, December.
    10. Loet Leydesdorff, 2007. "Betweenness centrality as an indicator of the interdisciplinarity of scientific journals," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(9), pages 1303-1319, July.
    11. Loet Leydesdorff, 2007. "Visualization of the citation impact environments of scientific journals: An online mapping exercise," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(1), pages 25-38, January.
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