A cluster analysis of scholar and journal bibliometric indicators

  • Authors:
  • Massimo Franceschet

  • Affiliations:
  • Department of Mathematics and Computer Science, University of Udine, Via delle Scienze, 206–33100 Udine, Italy

  • Venue:
  • Journal of the American Society for Information Science and Technology
  • Year:
  • 2009

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Abstract

We investigate different approaches based on correlation analysis to reduce the complexity of a space of quantitative indicators for the assessment of research performance. The proposed methods group bibliometric indicators into clusters of highly intercorrelated indicators. Each cluster is then associated with a representative indicator. The set of all representatives corresponds to a base of orthogonal metrics capturing independent aspects of research performance and can be exploited to design a composite performance indicator. We apply the devised methodology to isolate orthogonal performance metrics for scholars and journals in the field of computer science and to design a global performance indicator. The methodology is general and can be exploited to design composite indicators that are based on a set of possibly overlapping criteria. © 2009 Wiley Periodicals, Inc.