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Sharing information in web communities

Author

Listed:
  • Gabrielle Demange

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris-Jourdan Sciences Economiques - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique)

Abstract

The paper investigates information sharing communities. The environment is characterized by the anonymity of the contributors and users, as on the Web. It is argued that a community may be worth forming because it facilitates the interpretation and understanding of the posted information. The admission within a community and the stability of multiple communities are examined when individuals differ in their tastes.

Suggested Citation

  • Gabrielle Demange, 2009. "Sharing information in web communities," PSE Working Papers halshs-00586656, HAL.
    • Handle: RePEc:hal:psewpa:halshs-00586656
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00586656v1
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    File URL: https://shs.hal.science/halshs-00586656v1/document
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    Cited by:

    1. is not listed on IDEAS
    2. Angelo Antoci & Fabio Sabatini & Mauro Sodini, 2014. "Bowling alone but tweeting together: the evolution of human interaction in the social networking era," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 1911-1927, July.
    3. Daniel Sgroi & Andrew J. Oswald, 2013. "How Should Peer‐review Panels Behave?," Economic Journal, Royal Economic Society, vol. 0, pages 255-278, August.
    4. Gill, David & Sgroi, Daniel, 2012. "The optimal choice of pre-launch reviewer," Journal of Economic Theory, Elsevier, vol. 147(3), pages 1247-1260.
    5. Gill, David & Sgroi, Daniel, "undated". "The Optimal Choice of Pre-launch Reviewer: How Best to Transmit Information using Tests and Conditional Pricing," Economic Research Papers 269888, University of Warwick - Department of Economics.

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