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On the influence of a ranking system

Author

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  • Gabrielle Demange

    (PSE - Paris-Jourdan Sciences Economiques - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

Ranking systems are becoming increasingly important in many areas, in the Web environment and academic life for instance. In a world with a tremendous amount of choices, rankings play the crucial role of influencing which objects are tasted or selected. This selection generates a feedback when the ranking is based on citations, as is the case for the widely used invariant method. The selection affects new stated opinions (citations), which will, in turn, affect the next ranking. The purpose of this paper is to investigate this feedback in the context of journals by studying some simple but reasonable dynamics. Our main interest is in the long run behavior of the process and how it depends on the preferences, in particular on their diversity. We show that multiple long run behaviors may arise due to strong self-reinforcing mechanisms at work with the invariant method. These effects are not present in a simple search model in which individuals are influenced by the cites of the papers they first read.

Suggested Citation

  • Gabrielle Demange, 2012. "On the influence of a ranking system," PSE-Ecole d'économie de Paris (Postprint) halshs-00754615, HAL.
    • Handle: RePEc:hal:pseptp:halshs-00754615
    DOI: 10.1007/s00355-011-0631-5
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    References listed on IDEAS

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    Cited by:

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    3. Germano, Fabrizio & Sobbrio, Francesco, 2020. "Opinion dynamics via search engines (and other algorithmic gatekeepers)," Journal of Public Economics, Elsevier, vol. 187(C).
    4. Brink, René van den & Rusinowska, Agnieszka, 2021. "The degree ratio ranking method for directed graphs," European Journal of Operational Research, Elsevier, vol. 288(2), pages 563-575.

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