IDEAS home Printed from https://ideas.repec.org/a/spr/jcsosc/v6y2023i2d10.1007_s42001-023-00225-8.html
   My bibliography  Save this article

Bridging the offline and online: 20 years of offline meeting data of the German-language Wikipedia

Author

Listed:
  • Nicole Schwitter

    (University of Warwick)

Abstract

Wikipedia is one of the most visited websites worldwide. Thousands of volunteers are contributing to it daily, making it an example of how productive non-market collaboration on a very wide scale is not only viable but also sustainable. Wikipedia’s freely available data on the online actions conducted make it a popular source of data, particularly for computer scientists and computational social scientists. This data brief will present the dewiki meetup dataset which covers the offline component of the German-language version of the online encyclopaedia Wikipedia: informal offline gatherings between Wikipedia contributors. These gatherings are organised online and information about who is attending them, where they take place and what has happened at these meetings is shared publicly. The dewiki meetup dataset covers almost 20 years of offline activity of the German-language Wikipedia, containing 4418 meetups that have been organised with information on attendees, apologies, date and place of meeting, and minutes recorded. It is a valuable source of data for social science research: it captures the development of the offline network over time of one of the largest and most sustainable online public goods and communities. The data can easily be merged with online activity data on Wikipedia which allows us to bridge the gap between offline and online behaviour.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:jcsosc:v:6:y:2023:i:2:d:10.1007_s42001-023-00225-8
    DOI: 10.1007/s42001-023-00225-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s42001-023-00225-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s42001-023-00225-8?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.

    References listed on IDEAS

    as
    1. Ewa S. Callahan & Susan C. Herring, 2011. "Cultural bias in Wikipedia content on famous persons," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(10), pages 1899-1915, October.
    2. Jim Giles, 2005. "Internet encyclopaedias go head to head," Nature, Nature, vol. 438(7070), pages 900-901, December.
    3. Noriko Hara & Pnina Shachaf & Khe Foon Hew, 2010. "Cross-cultural analysis of the Wikipedia community," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(10), pages 2097-2108, October.
    4. Márton Mestyán & Taha Yasseri & János Kertész, 2013. "Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    5. Noriko Hara & Pnina Shachaf & Khe Foon Hew, 2010. "Cross‐cultural analysis of the Wikipedia community," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(10), pages 2097-2108, October.
    6. 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.
    7. Xiaoquan (Michael) Zhang & Feng Zhu, 2011. "Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia," American Economic Review, American Economic Association, vol. 101(4), pages 1601-1615, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nicolas Jullien, 2012. "What We Know About Wikipedia: A Review of the Literature Analyzing the Project(s)," Post-Print hal-00857208, HAL.
    2. Kevin Crowston & Nicolas Jullien & Felipe Ortega, 2013. "Is Wikipedia Inefficient? Modelling Effort and Participation in Wikipedia," Post-Print hal-00947731, HAL.
    3. 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.
    4. 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.
    5. Anna Kerkhof & Johannes Münster, 2021. "Detecting Coverage Bias in User-Generated Content," CESifo Working Paper Series 8844, CESifo.
    6. 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.
    7. Aaltonen, Aleksi Ville & Seiler, Stephan, 2014. "Quantifying spillovers in open source content production: evidence from Wikipedia," LSE Research Online Documents on Economics 60284, London School of Economics and Political Science, LSE Library.
    8. Charles Ayoubi & Boris Thurm, 2023. "Knowledge diffusion and morality: Why do we freely share valuable information with Strangers?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 32(1), pages 75-99, January.
    9. Hervé, Fabrice & Zouaoui, Mohamed & Belvaux, Bertrand, 2019. "Noise traders and smart money: Evidence from online searches," Economic Modelling, Elsevier, vol. 83(C), pages 141-149.
    10. 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," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-9, December.
    11. Shane Greenstein & Grace Gu & Feng Zhu, 2021. "Ideology and Composition Among an Online Crowd: Evidence from Wikipedians," Management Science, INFORMS, vol. 67(5), pages 3067-3086, May.
    12. Sheen S. Levine & Michael J. Prietula, 2014. "Open Collaboration for Innovation: Principles and Performance," Organization Science, INFORMS, vol. 25(5), pages 1414-1433, October.
    13. Safner, Ryan, 2016. "Institutional entrepreneurship, wikipedia, and the opportunity of the commons," Journal of Institutional Economics, Cambridge University Press, vol. 12(4), pages 743-771, December.
    14. 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.
    15. 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.
    16. Shane Greenstein & Feng Zhu, 2016. "Open Content, Linus’ Law, and Neutral Point of View," Information Systems Research, INFORMS, vol. 27(3), pages 618-635.
    17. Aleksi Aaltonen & Stephan Seiler, 2014. "Quantifying Spillovers in Open Source Content Production: Evidence from Wikipedia," CEP Discussion Papers dp1275, Centre for Economic Performance, LSE.
    18. Arthur Schram & Boris Van Leeuwen & Theo Offerman, 2013. "Superstars Need Social Benefits: An Experiment on Network Formation," Working Papers 1306, Departament Empresa, Universitat Autònoma de Barcelona, revised Jul 2013.
    19. Wei Luo & Julia Adams & Hannah Brueckner, 2018. "The Ladies Vanish? American Sociology and the Genealogy of its Missing Women on Wikipedia," Working Papers 20180012, New York University Abu Dhabi, Department of Social Science, revised Jan 2018.
    20. Shane Greenstein & Yuan Gu & Feng Zhu, 2016. "Ideological Segregation among Online Collaborators: Evidence from Wikipedians," Harvard Business School Working Papers 17-028, Harvard Business School, revised Mar 2017.

    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:jcsosc:v:6:y:2023:i:2:d:10.1007_s42001-023-00225-8. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.