Behavioral Aspects of Learning in Social Networks: An Experimental Study

Syngjoo Choi, Douglas Gale, Shachar Kariv

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Abstract

    Networks are natural tools for understanding social and economic phenomena. For example, all markets are characterized by agents connected by complex, multilateral information networks, and the network structure influences economic outcomes. In an earlier study, we undertook an experimental investigation of learning in various three-person networks, each of which gives rise to its own learning patterns. In the laboratory, learning in networks is challenging and the difficulty of solving the decision problem is sometimes massive even in the case of three persons. We found that the theory can account surprisingly well for the behavior observed in the laboratory. The aim of the present paper is to investigate important and interesting questions about individual and group behavior, including comparisons across networks and information treatments. We find that in order to explain subjects' behavior, it is necessary to take into account the details of the network architecture as well as the information structure. We also identify some "black spots" where the theory does least well in interpreting the data.

    Original languageEnglish (US)
    Title of host publicationExperimental and Behavorial Economics
    EditorsJohn Morgan
    Pages25-61
    Number of pages37
    DOIs
    StatePublished - 2005

    Publication series

    NameAdvances in Applied Microeconomics
    Volume13
    ISSN (Print)0278-0984

    ASJC Scopus subject areas

    • Economics, Econometrics and Finance (miscellaneous)

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