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A cluster analysis of scholar and journal bibliometric indicators

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  • Massimo Franceschet

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.

Suggested Citation

  • Massimo Franceschet, 2009. "A cluster analysis of scholar and journal bibliometric indicators," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(10), pages 1950-1964, October.
    • Handle: RePEc:bla:jamist:v:60:y:2009:i:10:p:1950-1964
    DOI: 10.1002/asi.21152
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    Cited by:

    1. Gnewuch, Matthias & Wohlrabe, Klaus, 2018. "Super-efficiency of education institutions: an application to economics departments," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 26, pages 610-623.
    2. Bortoluzzi, Mirian & Correia de Souza, Celso & Furlan, Marcelo, 2021. "Bibliometric analysis of renewable energy types using key performance indicators and multicriteria decision models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    3. Franceschet, Massimo, 2010. "Journal influence factors," Journal of Informetrics, Elsevier, vol. 4(3), pages 239-248.
    4. Teodoro Luque-Martínez & Ignacio Luque-Raya, 2024. "Spanish scientific research by field and subject. Strategic analysis with ARWU indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5265-5285, September.
    5. Seiler, Christian & Wohlrabe, Klaus, 2013. "Archetypal scientists," Journal of Informetrics, Elsevier, vol. 7(2), pages 345-356.
    6. Ioana Alexandra HORODNIC, 2014. "Academic Performance: Measurement Methods Used In Socio - Economic Sciences," THE YEARBOOK OF THE "GH. ZANE" INSTITUTE OF ECONOMIC RESEARCHES, Gheorghe Zane Institute for Economic and Social Research ( from THE ROMANIAN ACADEMY, JASSY BRANCH), vol. 23(1), pages 5-17.
    7. Jiang Wu, 2013. "Geographical knowledge diffusion and spatial diversity citation rank," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 181-201, January.
    8. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2011. "National-scale research performance assessment at the individual level," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 347-364, February.
    9. Alfio Ferrara & Silvia Salini, 2012. "Ten challenges in modeling bibliographic data for bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 765-785, December.
    10. Agnieszka Saramak & Daniel Saramak, 2022. "Coal Modeling Investigations in International Collaboration in the Light of Bibliometric Analysis of the Problem," Energies, MDPI, vol. 15(16), pages 1-20, August.
    11. Bornmann, Lutz & Mutz, Rüdiger & Hug, Sven E. & Daniel, Hans-Dieter, 2011. "A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants," Journal of Informetrics, Elsevier, vol. 5(3), pages 346-359.
    12. Walters, William H., 2017. "Do subjective journal ratings represent whole journals or typical articles? Unweighted or weighted citation impact?," Journal of Informetrics, Elsevier, vol. 11(3), pages 730-744.
    13. Seiler, Christian & Wohlrabe, Klaus, 2012. "Ranking economists on the basis of many indicators: An alternative approach using RePEc data," Journal of Informetrics, Elsevier, vol. 6(3), pages 389-402.
    14. Tuomas Höylä & Christoph Bartneck & Timo Tiihonen, 2016. "The consequences of competition: simulating the effects of research grant allocation strategies," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 263-288, July.
    15. H. Kent Baker & Satish Kumar & Kirti Goyal & Prashant Gupta, 2023. "International journal of finance and economics: A bibliometric overview," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 9-46, January.
    16. Seiler, Christian & Wohlrabe, Klaus, 2012. "Ranking economists on the basis of many indicators: An alternative approach using RePEc data," Journal of Informetrics, Elsevier, vol. 6(3), pages 389-402.
    17. Lutz Bornmann & Alexander Butz & Klaus Wohlrabe, 2018. "What are the top five journals in economics? A new meta-ranking," Applied Economics, Taylor & Francis Journals, vol. 50(6), pages 659-675, February.
    18. Hall, C. Michael & Page, Stephen J., 2015. "Following the impact factor: Utilitarianism or academic compliance?," Tourism Management, Elsevier, vol. 51(C), pages 309-312.
    19. Michael Hall, C., 2011. "Publish and perish? Bibliometric analysis, journal ranking and the assessment of research quality in tourism," Tourism Management, Elsevier, vol. 32(1), pages 16-27.
    20. Rodrigo Costas & Thed N. Leeuwen & María Bordons, 2012. "Referencing patterns of individual researchers: Do top scientists rely on more extensive information sources?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2433-2450, December.

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