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
    Pages25-61
    Number of pages37
    Volume13
    DOIs
    StatePublished - 2005

    Publication series

    NameAdvances in Applied Microeconomics
    Volume13
    ISSN (Print)02780984

    Fingerprint

    Experimental study
    Social networks
    Economics
    Network structure
    Information networks
    Individual behaviour
    Group behavior
    Information structure

    ASJC Scopus subject areas

    • Economics, Econometrics and Finance (miscellaneous)

    Cite this

    Choi, S., Gale, D., & Kariv, S. (2005). Behavioral Aspects of Learning in Social Networks: An Experimental Study. In Experimental and Behavorial Economics (Vol. 13, pp. 25-61). (Advances in Applied Microeconomics; Vol. 13). https://doi.org/10.1016/S0278-0984(05)13002-8

    Behavioral Aspects of Learning in Social Networks : An Experimental Study. / Choi, Syngjoo; Gale, Douglas; Kariv, Shachar.

    Experimental and Behavorial Economics. Vol. 13 2005. p. 25-61 (Advances in Applied Microeconomics; Vol. 13).

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Choi, S, Gale, D & Kariv, S 2005, Behavioral Aspects of Learning in Social Networks: An Experimental Study. in Experimental and Behavorial Economics. vol. 13, Advances in Applied Microeconomics, vol. 13, pp. 25-61. https://doi.org/10.1016/S0278-0984(05)13002-8
    Choi S, Gale D, Kariv S. Behavioral Aspects of Learning in Social Networks: An Experimental Study. In Experimental and Behavorial Economics. Vol. 13. 2005. p. 25-61. (Advances in Applied Microeconomics). https://doi.org/10.1016/S0278-0984(05)13002-8
    Choi, Syngjoo ; Gale, Douglas ; Kariv, Shachar. / Behavioral Aspects of Learning in Social Networks : An Experimental Study. Experimental and Behavorial Economics. Vol. 13 2005. pp. 25-61 (Advances in Applied Microeconomics).
    @inbook{6eef18db768a4a64a1c0cb841172560e,
    title = "Behavioral Aspects of Learning in Social Networks: An Experimental Study",
    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.",
    author = "Syngjoo Choi and Douglas Gale and Shachar Kariv",
    year = "2005",
    doi = "10.1016/S0278-0984(05)13002-8",
    language = "English (US)",
    isbn = "0762311940",
    volume = "13",
    series = "Advances in Applied Microeconomics",
    pages = "25--61",
    booktitle = "Experimental and Behavorial Economics",

    }

    TY - CHAP

    T1 - Behavioral Aspects of Learning in Social Networks

    T2 - An Experimental Study

    AU - Choi, Syngjoo

    AU - Gale, Douglas

    AU - Kariv, Shachar

    PY - 2005

    Y1 - 2005

    N2 - 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.

    AB - 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.

    UR - http://www.scopus.com/inward/record.url?scp=33645920658&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=33645920658&partnerID=8YFLogxK

    U2 - 10.1016/S0278-0984(05)13002-8

    DO - 10.1016/S0278-0984(05)13002-8

    M3 - Chapter

    SN - 0762311940

    SN - 9780762311941

    VL - 13

    T3 - Advances in Applied Microeconomics

    SP - 25

    EP - 61

    BT - Experimental and Behavorial Economics

    ER -