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User science indicators in the Web context and co-usage analysis

Author

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  • Xavier Polanco

    (Unité de Recherche et Innovation, Institut de l'Information Scientifique et Technique, Centre National de la Recherche Scientifique)

  • Roche Ivana

    (Unité de Recherche et Innovation, Institut de l'Information Scientifique et Technique, Centre National de la Recherche Scientifique)

  • Besagni Dominique

    (Unité de Recherche et Innovation, Institut de l'Information Scientifique et Technique, Centre National de la Recherche Scientifique)

Abstract

Summary We present a new kind of statistical analysis of science and technical information (STI) in the Web context. We propose a battery of indicators about Web users, used bibliographic records and e-commercial transactions. In addition, we introduce two Web usage factors and we give an overview of the co-usage analysis. For these tasks, we present a computer-based system, called Miri@d, which produces descriptive statistical information about Web users' searching behaviour, and what is effectively used from a free-access digital bibliographical database.

Suggested Citation

  • Xavier Polanco & Roche Ivana & Besagni Dominique, 2006. "User science indicators in the Web context and co-usage analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 66(1), pages 171-182, January.
    • Handle: RePEc:spr:scient:v:66:y:2006:i:1:d:10.1007_s11192-006-0012-5
    DOI: 10.1007/s11192-006-0012-5
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    Cited by:

    1. Kraker, Peter & Schlögl, Christian & Jack, Kris & Lindstaedt, Stefanie, 2015. "Visualization of co-readership patterns from an online reference management system," Journal of Informetrics, Elsevier, vol. 9(1), pages 169-182.
    2. David Gunnarsson Lorentzen, 2014. "Webometrics benefitting from web mining? An investigation of methods and applications of two research fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 409-445, May.

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