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Targeted vs. collective information sharing in networks

Author

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  • Alexey Kushnir
  • Alexandru Nichifor

Abstract

We introduce a simple two-stage game of endogenous network formation and information sharing for reasoning about the optimal design of social networks like Facebook or Google+. We distinguish between unilateral and bilateral connections and between targeted and collective information sharing. Agents value being connected to other agents and sharing and receiving information. We consider multiple utility specifications. We show that the game always has an equilibrium in pure strategies and then we study how the network design and the utility specifications affect welfare. Surprisingly, we find that in general, targeted information sharing is not necessarily better than collective information sharing. However, if all agents are either "babblers" or "friends", irrespective of whether the network is unilateral or bilateral, in equilibrium, targeted information sharing yields higher welfare than collective information sharing.

Suggested Citation

  • Alexey Kushnir & Alexandru Nichifor, 2014. "Targeted vs. collective information sharing in networks," ECON - Working Papers 152, Department of Economics - University of Zurich.
  • Handle: RePEc:zur:econwp:152
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    File URL: http://www.econ.uzh.ch/static/wp/econwp152.pdf
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    References listed on IDEAS

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    1. Pagano, Marco & Jappelli, Tullio, 1993. " Information Sharing in Credit Markets," Journal of Finance, American Finance Association, vol. 48(5), pages 1693-1718, December.
    2. Masahiro Okuno-Fujiwara & Andrew Postlewaite & Kotaro Suzumura, 1990. "Strategic Information Revelation," Review of Economic Studies, Oxford University Press, vol. 57(1), pages 25-47.
    3. Jackson, Matthew O. & Wolinsky, Asher, 1996. "A Strategic Model of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 71(1), pages 44-74, October.
    4. Echenique, Federico & Oviedo, Jorge, 2006. "A theory of stability in many-to-many matching markets," Theoretical Economics, Econometric Society, vol. 1(2), pages 233-273, June.
    5. Kim, Chongmin & Wong, Kam-Chau, 2007. "Network formation and stable equilibrium," Journal of Economic Theory, Elsevier, vol. 133(1), pages 536-549, March.
    6. Venkatesh Bala & Sanjeev Goyal, 2000. "A Noncooperative Model of Network Formation," Econometrica, Econometric Society, vol. 68(5), pages 1181-1230, September.
    7. Michael Ostrovsky & Michael Schwarz, 2010. "Information Disclosure and Unraveling in Matching Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 2(2), pages 34-63, May.
    8. Galeotti, Andrea & Goyal, Sanjeev & Kamphorst, Jurjen, 2006. "Network formation with heterogeneous players," Games and Economic Behavior, Elsevier, vol. 54(2), pages 353-372, February.
    9. Kleinberg, Jon & Ligett, Katrina, 2013. "Information-sharing in social networks," Games and Economic Behavior, Elsevier, vol. 82(C), pages 702-716.
    10. Dutta, Bhaskar & Mutuswami, Suresh, 1997. "Stable Networks," Journal of Economic Theory, Elsevier, vol. 76(2), pages 322-344, October.
      • Dutta, Bhaskar & Mutuswami, Suresh, 1996. "Stable Networks," Working Papers 971, California Institute of Technology, Division of the Humanities and Social Sciences.
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    More about this item

    Keywords

    Networks; network formation; unilateral connections; bilateral connections; targeted information sharing; collective information sharing; Google; Facebook; babblers; friends;

    JEL classification:

    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium

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