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World influence and interactions of universities from Wikipedia networks

Author

Listed:
  • Célestin Coquidé

    (Institut UTINAM, Observatoire des Sciences de l’Univers THETA, CNRS, Université de Bourgogne Franche-Comté)

  • José Lages

    (Institut UTINAM, Observatoire des Sciences de l’Univers THETA, CNRS, Université de Bourgogne Franche-Comté)

  • Dima L. Shepelyansky

    (Laboratoire de Physique Théorique, IRSAMC, Université de Toulouse, CNRS, UPS)

Abstract

We present Wikipedia Ranking of World Universities (WRWU) based on analysis of networks of 24 Wikipedia editions collected in May 2017. With PageRank and CheiRank algorithms we determine ranking of universities averaged over cultural views of these editions. The comparison with the Shanghai ranking gives overlap of 60% for top 100 universities showing that WRWU gives more significance to their historical development. We show that the new reduced Google matrix algorithm allows to determine interactions between leading universities on a scale of ten centuries. This approach also determines the influence of specific universities on world countries. We also compare different cultural views of Wikipedia editions on significance and influence of universities. Graphical abstract

Suggested Citation

  • Célestin Coquidé & José Lages & Dima L. Shepelyansky, 2019. "World influence and interactions of universities from Wikipedia networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 92(1), pages 1-20, January.
    • Handle: RePEc:spr:eurphb:v:92:y:2019:i:1:d:10.1140_epjb_e2018-90532-7
    DOI: 10.1140/epjb/e2018-90532-7
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    Citations

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    Cited by:

    1. Andrei Zinovyev & Urszula Czerwinska & Laura Cantini & Emmanuel Barillot & Klaus M Frahm & Dima L Shepelyansky, 2020. "Collective intelligence defines biological functions in Wikipedia as communities in the hidden protein connection network," PLOS Computational Biology, Public Library of Science, vol. 16(2), pages 1-19, February.
    2. Demidov, Denis & Frahm, Klaus M. & Shepelyansky, Dima L., 2020. "What is the central bank of Wikipedia?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    3. C'elestin Coquid'e & Leonardo Ermann & Jos'e Lages & D. L. Shepelyansky, 2019. "Influence of petroleum and gas trade on EU economies from the reduced Google matrix analysis of UN COMTRADE data," Papers 1903.01820, arXiv.org.
    4. Denis Demidov & Klaus M. Frahm & Dima L. Shepelyansky, 2019. "What is the central bank of Wikipedia?," Papers 1902.07920, arXiv.org.
    5. Célestin Coquidé & José Lages & Dima Shepelyansky, 2020. "Interdependence of sectors of economic activities for world countries from the reduced Google matrix analysis of WTO data," Post-Print hal-02132487, HAL.
    6. Frahm, Klaus M. & Shepelyansky, Dima L., 2020. "Google matrix analysis of bi-functional SIGNOR network of protein–protein interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).

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    Keywords

    Statistical and Nonlinear Physics;

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