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Spillovers in networks of user generated content: Evidence from 23 natural experiments on Wikipedia

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  • Kummer, Michael E.

Abstract

Endogeneity in network formation hinders the identification of the role social networks play in generating spillovers, peer effects and other externalities. This paper tackles this problem and investigates how the link network between articles on the German Wikipedia influences the attention and content generation individual articles receive. Identification exploits local exogenous shocks on a small number of nodes in the network. It can thus avoid the usually required, but strong, assumptions of exogenous observed characteristics and link structure in networks. This approach also applies if, due to a lack of network information, identification through partial overlaps in the network structure fails (e.g. in classrooms). Exogenous variation is generated by natural and technical disasters or by articles being featured on the German Wikipedia's start page. The effects on neighboring pages are substantial; I observe an increase of almost 100 percent in terms of both views and content generation. The aggregate effect over all neighbors is also large: I find that a view on a treated article converts one for one into a view on a neighboring article. However, the resulting content generation is small in absolute terms.

Suggested Citation

  • Kummer, Michael E., 2013. "Spillovers in networks of user generated content: Evidence from 23 natural experiments on Wikipedia," ZEW Discussion Papers 13-098, ZEW - Leibniz Centre for European Economic Research.
  • Handle: RePEc:zbw:zewdip:13098
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    Cited by:

    1. Slivko, Olga, 2014. "Peer effects in collaborative content generation: The evidence from German Wikipedia," ZEW Discussion Papers 14-128, ZEW - Leibniz Centre for European Economic Research.
    2. Aleksi Aaltonen & Stephan Seiler, 2016. "Cumulative Growth in User-Generated Content Production: Evidence from Wikipedia," Management Science, INFORMS, vol. 62(7), pages 2054-2069, July.
    3. Abhishek Nagaraj, 2021. "Information Seeding and Knowledge Production in Online Communities: Evidence from OpenStreetMap," Management Science, INFORMS, vol. 67(8), pages 4908-4934, August.

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    More about this item

    Keywords

    Social Media; Information; Knowledge; Spillovers; Large-scale Networks; Natural Experiment;
    All these keywords.

    JEL classification:

    • L17 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Open Source Products and Markets
    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • D29 - Microeconomics - - Production and Organizations - - - Other

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