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Cultural bias in Wikipedia content on famous persons

Author

Listed:
  • Ewa S. Callahan
  • Susan C. Herring

Abstract

Wikipedia advocates a strict “neutral point of view” (NPOV) policy. However, although originally a U.S‐based, English‐language phenomenon, the online, user‐created encyclopedia now has versions in many languages. This study examines the extent to which content and perspectives vary across cultures by comparing articles about famous persons in the Polish and English editions of Wikipedia. The results of quantitative and qualitative content analyses reveal systematic differences related to the different cultures, histories, and values of Poland and the United States; at the same time, a U.S./English‐language advantage is evident throughout. In conclusion, the implications of these findings for the quality and objectivity of Wikipedia as a global repository of knowledge are discussed, and recommendations are advanced for Wikipedia end users and content developers.

Suggested Citation

  • Ewa S. Callahan & Susan C. Herring, 2011. "Cultural bias in Wikipedia content on famous persons," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1899-1915, October.
    • Handle: RePEc:bla:jamist:v:62:y:2011:i:10:p:1899-1915
    DOI: 10.1002/asi.21577
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    References listed on IDEAS

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    1. Jim Giles, 2005. "Internet encyclopaedias go head to head," Nature, Nature, vol. 438(7070), pages 900-901, December.
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    Cited by:

    1. Jaehun Joo & Ismatilla Normatov, 2013. "Determinants of collective intelligence quality: comparison between Wiki and Q&A services in English and Korean users," Service Business, Springer;Pan-Pacific Business Association, vol. 7(4), pages 687-711, December.
    2. Dwaipayan Roy & Sumit Bhatia & Prateek Jain, 2022. "Information asymmetry in Wikipedia across different languages: A statistical analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(3), pages 347-361, March.
    3. Nicolas Jullien, 2012. "What We Know About Wikipedia: A Review of the Literature Analyzing the Project(s)," Post-Print hal-00857208, HAL.
    4. Xiang Zheng & Jiajing Chen & Erjia Yan & Chaoqun Ni, 2023. "Gender and country biases in Wikipedia citations to scholarly publications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(2), pages 219-233, February.
    5. Nicole Schwitter, 2023. "Bridging the offline and online: 20 years of offline meeting data of the German-language Wikipedia," Journal of Computational Social Science, Springer, vol. 6(2), pages 1103-1124, October.
    6. Philipp Koch & Viktor Stojkoski & César A. Hidalgo, 2024. "Augmenting the availability of historical GDP per capita estimates through machine learning," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 121(39), pages 2402060121-, September.
    7. Anna Kerkhof & Johannes Münster, 2021. "Detecting Coverage Bias in User-Generated Content," CESifo Working Paper Series 8844, CESifo.
    8. José Gustavo Góngora-Goloubintseff, 2020. "The Falklands/Malvinas war taken to the Wikipedia realm: a multimodal discourse analysis of cross-lingual violations of the Neutral Point of View," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 6(1), pages 1-9, December.
    9. Anna Kerkhof & Johannes Münster, 2021. "Detecting coverage bias in user-generated content," ECONtribute Discussion Papers Series 057, University of Bonn and University of Cologne, Germany.
    10. Patrick Gildersleve & Renaud Lambiotte & Taha Yasseri, 2023. "Between news and history: identifying networked topics of collective attention on Wikipedia," Journal of Computational Social Science, Springer, vol. 6(2), pages 845-875, October.
    11. Kevin Crowston & Nicolas Jullien & Felipe Ortega, 2013. "Is Wikipedia Inefficient? Modelling Effort and Participation in Wikipedia," Post-Print hal-00947731, HAL.

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