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Ranking Institutions within a Discipline: The Steep Mountain of Academic Excellence

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  • Balázs R. Sziklai

    (Institute of Economics, Centre for Economic and Regional Studies, Hungary and Department of Operations Research and Actuarial Sciences, Corvinus University of Budapest, Hungary)

Abstract

We present a novel algorithm to rank smaller academic entities such as university departments or research groups within a research discipline. The Weighted Top Candidate (WTC) algorithm is a generalisation of an expert identification method. The axiomatic characterisation of WTC shows why it is especially suitable for scientometric purposes. The key axiom is stability -- the selected institutions support each other's membership. The WTC algorithm, upon receiving an institution citation matrix, produces a list of institutions that can be deemed experts of the field. With a parameter we can adjust how exclusive our list should be. By completely relaxing the parameter, we obtain the largest stable set -- academic entities that can qualify as experts under the mildest conditions. With a strict setup, we obtain a short list of the absolute elite. We demonstrate the algorithm on a citation database compiled from game theoretic literature published between 2008--2017. By plotting the size of the stable sets with respect to exclusiveness, we can obtain an overview of the competitiveness of the field. The diagram hints at how difficult it is for an institution to improve its position.

Suggested Citation

  • Balázs R. Sziklai, 2021. "Ranking Institutions within a Discipline: The Steep Mountain of Academic Excellence," CERS-IE WORKING PAPERS 2106, Institute of Economics, Centre for Economic and Regional Studies.
  • Handle: RePEc:has:discpr:2106
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    References listed on IDEAS

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    Cited by:

    1. Xiang Li & Chengli Zhao & Zhaolong Hu & Caixia Yu & Xiaojun Duan, 2022. "Revealing the character of journals in higher-order citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6315-6338, November.
    2. Ádám Ipkovich & Károly Héberger & János Abonyi, 2021. "Comprehensible Visualization of Multidimensional Data: Sum of Ranking Differences-Based Parallel Coordinates," Mathematics, MDPI, vol. 9(24), pages 1-17, December.
    3. Cena, Anna & Gagolewski, Marek & Siudem, Grzegorz & Żogała-Siudem, Barbara, 2022. "Validating citation models by proxy indices," Journal of Informetrics, Elsevier, vol. 16(2).

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    More about this item

    Keywords

    University departments; Ranking; Weighted Top Candidate method; Research discipline;
    All these keywords.

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations

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