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Social learning by chit-chat

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  • Gallo, Edoardo

Abstract

Individuals learn by chit-chatting with others as a by-product of their online and offline activities. Social plugins are an example in the online context: they embed information from a friend, acquaintance or even a stranger on a web page and the information is usually independent of the content of the web page. We formulate a novel framework to investigate how the speed of learning by chit-chat depends on the structure of the environment. A network represents the environment that individuals navigate to interact with each other. We derive an exact formula to compute how the expected time between meetings depends on the underlying network structure and we use this quantity to investigate the speed of learning in the society. Comparative statics show that the speed of learning is sensitive to a mean-preserving spread of the degree distribution (MPS). Specifically, if the number of individuals is low (high), then a MPS of the network increases (decreases) the speed of learning. The speed of learning is the same for all regular networks independent of network connectivity. An extension explores the effectiveness of one agent, the influencer, at influencing the learning process.

Suggested Citation

  • Gallo, Edoardo, 2014. "Social learning by chit-chat," Journal of Economic Theory, Elsevier, vol. 153(C), pages 313-343.
    • Handle: RePEc:eee:jetheo:v:153:y:2014:i:c:p:313-343
    DOI: 10.1016/j.jet.2014.07.007
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    References listed on IDEAS

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    1. Lamberson PJ, 2010. "Social Learning in Social Networks," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 10(1), pages 1-33, August.
    2. Acemoglu, Daron & Ozdaglar, Asuman & ParandehGheibi, Ali, 2010. "Spread of (mis)information in social networks," Games and Economic Behavior, Elsevier, vol. 70(2), pages 194-227, November.
    3. Jackson Matthew O. & Rogers Brian W., 2007. "Relating Network Structure to Diffusion Properties through Stochastic Dominance," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 7(1), pages 1-16, February.
    4. Venkatesh Bala & Sanjeev Goyal, 1998. "Learning from Neighbours," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 595-621.
    5. Peter M. DeMarzo & Dimitri Vayanos & Jeffrey Zwiebel, 2003. "Persuasion Bias, Social Influence, and Unidimensional Opinions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(3), pages 909-968.
    6. López-Pintado, Dunia, 2008. "Diffusion in complex social networks," Games and Economic Behavior, Elsevier, vol. 62(2), pages 573-590, March.
    7. Matthew O. Jackson & Brian W. Rogers, 2007. "Meeting Strangers and Friends of Friends: How Random Are Social Networks?," American Economic Review, American Economic Association, vol. 97(3), pages 890-915, June.
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    Cited by:

    1. Edoardo Gallo & Alastair Langtry, 2020. "Social networks, confirmation bias and shock elections," Papers 2011.00520, arXiv.org.
    2. Dessí, Roberta & Gallo, Edoardo & Goyal, Sanjeev, 2016. "Network cognition," Journal of Economic Behavior & Organization, Elsevier, vol. 123(C), pages 78-96.
    3. Goyal, S., 2016. "Networks and Markets," Cambridge Working Papers in Economics 1652, Faculty of Economics, University of Cambridge.
    4. Gallo, E. & Langtry, A., 2020. "Social Networks, Confirmation Bias and Shock Elections," Cambridge Working Papers in Economics 2099, Faculty of Economics, University of Cambridge.

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    More about this item

    Keywords

    Social learning; Network; Speed of learning; Mean preserving spread; Influencer;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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