IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v77y2010i4p523-531.html
   My bibliography  Save this article

Two-dimensional ranking of Wikipedia articles

Author

Listed:
  • A. O. Zhirov
  • O. V. Zhirov
  • D. L. Shepelyansky

Abstract

The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists ab aeterno. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. While PageRank highlights very well known nodes with many ingoing links, CheiRank highlights very communicative nodes with many outgoing links. In this way the ranking becomes two-dimensional. Using CheiRank and PageRank we analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories. Copyright EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2010

Suggested Citation

  • A. O. Zhirov & O. V. Zhirov & D. L. Shepelyansky, 2010. "Two-dimensional ranking of Wikipedia articles," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 77(4), pages 523-531, October.
    • Handle: RePEc:spr:eurphb:v:77:y:2010:i:4:p:523-531
    DOI: 10.1140/epjb/e2010-10500-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1140/epjb/e2010-10500-7
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1140/epjb/e2010-10500-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Young-Ho Eom & Pablo Aragón & David Laniado & Andreas Kaltenbrunner & Sebastiano Vigna & Dima L Shepelyansky, 2015. "Interactions of Cultures and Top People of Wikipedia from Ranking of 24 Language Editions," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-27, March.
    2. Samer El Zant & Katia Jaffrès-Runser & Dima L Shepelyansky, 2018. "Capturing the influence of geopolitical ties from Wikipedia with reduced Google matrix," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-31, August.
    3. C'elestin Coquid'e & Jos'e Lages & Dima L. Shepelyansky, 2024. "Opinion formation in the world trade network," Papers 2401.02378, arXiv.org, revised Feb 2024.
    4. Vivek Kandiah & Hubert Escaith & Dima L. Shepelyansky, 2015. "Google matrix of the world network of economic activities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(7), pages 1-20, July.
    5. Young-Ho Eom & Dima L Shepelyansky, 2013. "Highlighting Entanglement of Cultures via Ranking of Multilingual Wikipedia Articles," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-10, October.
    6. 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.
    7. V. Kandiah & H. Escaith & D. L. Shepelyansky, 2015. "Contagion effects in the world network of economic activities," Papers 1507.03278, arXiv.org.
    8. 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.
    9. Célestin Coquidé & José Lages & Leonardo Ermann & Dima Shepelyansky, 2022. "COVID-19 impact on the international trade," Post-Print hal-03536528, HAL.
    10. Prathap, Gangan & Ujum, Ephrance Abu & Kumar, Sameer & Ratnavelu, Kuru, 2021. "Scoring the resourcefulness of researchers using bibliographic coupling patterns," Journal of Informetrics, Elsevier, vol. 15(3).
    11. Leonardo Ermann & Dima L. Shepelyansky, 2015. "Google matrix analysis of the multiproduct world trade network," Papers 1501.03371, arXiv.org.
    12. Guillaume Rollin & José Lages & Dima L Shepelyansky, 2019. "Wikipedia network analysis of cancer interactions and world influence," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-26, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:eurphb:v:77:y:2010:i:4:p:523-531. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.