A cluster analysis of scholar and journal bibliometric indicators

Massimo Franceschet

Journal of the American Society for Information Science and Technology, 2009, vol. 60, issue 10, 1950-1964

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.

Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jamist:v:60:y:2009:i:10:p:1950-1964

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