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Interactions of Cultures and Top People of Wikipedia from Ranking of 24 Language Editions

Author

Listed:
  • Young-Ho Eom
  • Pablo Aragón
  • David Laniado
  • Andreas Kaltenbrunner
  • Sebastiano Vigna
  • Dima L Shepelyansky

Abstract

Wikipedia is a huge global repository of human knowledge that can be leveraged to investigate interwinements between cultures. With this aim, we apply methods of Markov chains and Google matrix for the analysis of the hyperlink networks of 24 Wikipedia language editions, and rank all their articles by PageRank, 2DRank and CheiRank algorithms. Using automatic extraction of people names, we obtain the top 100 historical figures, for each edition and for each algorithm. We investigate their spatial, temporal, and gender distributions in dependence of their cultural origins. Our study demonstrates not only the existence of skewness with local figures, mainly recognized only in their own cultures, but also the existence of global historical figures appearing in a large number of editions. By determining the birth time and place of these persons, we perform an analysis of the evolution of such figures through 35 centuries of human history for each language, thus recovering interactions and entanglement of cultures over time. We also obtain the distributions of historical figures over world countries, highlighting geographical aspects of cross-cultural links. Considering historical figures who appear in multiple editions as interactions between cultures, we construct a network of cultures and identify the most influential cultures according to this network.

Suggested Citation

  • 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.
    • Handle: RePEc:plo:pone00:0114825
    DOI: 10.1371/journal.pone.0114825
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    References listed on IDEAS

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    1. 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.
    2. Leonardo Ermann & Dima L. Shepelyansky, 2011. "Google matrix of the world trade network," Papers 1103.5027, arXiv.org.
    3. Vivek Kandiah & Dima L Shepelyansky, 2013. "Google Matrix Analysis of DNA Sequences," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-10, May.
    4. 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.
    5. Linyuan Lü & Yi-Cheng Zhang & Chi Ho Yeung & Tao Zhou, 2011. "Leaders in Social Networks, the Delicious Case," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-9, June.
    6. Leonardo Ermann & Klaus Frahm & Dima Shepelyansky, 2013. "Spectral properties of Google matrix of Wikipedia and other networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(5), pages 1-10, May.
    7. Young-Ho Eom & Klaus M. Frahm & András Benczúr & Dima L. Shepelyansky, 2013. "Time evolution of Wikipedia network ranking," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(12), pages 1-9, December.
    8. Taha Yasseri & Robert Sumi & András Rung & András Kornai & János Kertész, 2012. "Dynamics of Conflicts in Wikipedia," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-12, June.
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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. Stephany, Fabian & Braesemann, Fabian, 2017. "An Exploration of Wikipedia Data as a Measure of Regional Knowledge Distribution," SocArXiv c2gd8, Center for Open Science.

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