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An Experimental Study of Persuasion Bias and Social Influence in Networks

Author

Listed:
  • Jordi Brandts

    (Institutd'AnalisiEconomica(CSIC)
    Barcelona GSE)

  • Ayça Ebru Giritligil

    (Murat Sertel Center for Advanced Economic Studies
    İstanbul Bilgi University)

  • Roberto A. Weber

    (Department of Economics, University of Zurich)

Abstract

In many areas of social life individuals receive information about a particular issue of interest from multiple sources. When these sources are connected through a network then proper aggregation of this information by an individual involves taking into account the structure of this network. The inability to aggregate properly may lead to various types of distortions. In our experiment a number of agents all want to find out the value of a particular parameter unknown to all. Agents receive private signals about the parameter and agents can communicate their estimates of the parameter repeatedly through a network, the structure of which is known by all players. We present results from experiments with four different networks. We find that the information of agents who have more outgoing links in a network gets more weight in the information aggregation of the other agents than it optimally should. Our results are consistent with the model of “persuasion bias” of De Marzo et al. (2003) and at odds with an alternative heuristic according to which the most influential agents are those with more incoming links.

Suggested Citation

  • Jordi Brandts & Ayça Ebru Giritligil & Roberto A. Weber, 2014. "An Experimental Study of Persuasion Bias and Social Influence in Networks," BELIS Working Papers 2014-03, BELIS, Istanbul Bilgi University.
    • Handle: RePEc:beb:wpbels:201403
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    References listed on IDEAS

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    Cited by:

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    2. Battiston, Pietro & Stanca, Luca, 2015. "Boundedly rational opinion dynamics in social networks: Does indegree matter?," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 400-421.
    3. Szeidl, Adam & Mobius, Markus & Phan, Tuan, 2015. "Treasure Hunt: Social Learning in the Field," CEPR Discussion Papers 10493, C.E.P.R. Discussion Papers.
    4. João V. Ferreira & Erik Schokkaert & Benoît Tarroux, 2023. "How group deliberation affects individual distributional preferences: An experimental study," Working Papers 2301, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
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    6. Mohsen Foroughifar, 2021. "Errors in Learning from Others' Choices," Papers 2105.01043, arXiv.org, revised Aug 2021.
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    8. Jakob Grazzini & Domenico Massaro, 2016. "Dispersed Information and the Origins of Aggregate Fluctuations," CESifo Working Paper Series 5957, CESifo.
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    More about this item

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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