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Contagion of Cooperation in Static and Fluid Social Networks

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  • Jillian J Jordan
  • David G Rand
  • Samuel Arbesman
  • James H Fowler
  • Nicholas A Christakis

Abstract

Cooperation is essential for successful human societies. Thus, understanding how cooperative and selfish behaviors spread from person to person is a topic of theoretical and practical importance. Previous laboratory experiments provide clear evidence of social contagion in the domain of cooperation, both in fixed networks and in randomly shuffled networks, but leave open the possibility of asymmetries in the spread of cooperative and selfish behaviors. Additionally, many real human interaction structures are dynamic: we often have control over whom we interact with. Dynamic networks may differ importantly in the goals and strategic considerations they promote, and thus the question of how cooperative and selfish behaviors spread in dynamic networks remains open. Here, we address these questions with data from a social dilemma laboratory experiment. We measure the contagion of both cooperative and selfish behavior over time across three different network structures that vary in the extent to which they afford individuals control over their network ties. We find that in relatively fixed networks, both cooperative and selfish behaviors are contagious. In contrast, in more dynamic networks, selfish behavior is contagious, but cooperative behavior is not: subjects are fairly likely to switch to cooperation regardless of the behavior of their neighbors. We hypothesize that this insensitivity to the behavior of neighbors in dynamic networks is the result of subjects’ desire to attract new cooperative partners: even if many of one’s current neighbors are defectors, it may still make sense to switch to cooperation. We further hypothesize that selfishness remains contagious in dynamic networks because of the well-documented willingness of cooperators to retaliate against selfishness, even when doing so is costly. These results shed light on the contagion of cooperative behavior in fixed and fluid networks, and have implications for influence-based interventions aiming at increasing cooperative behavior.

Suggested Citation

  • Jillian J Jordan & David G Rand & Samuel Arbesman & James H Fowler & Nicholas A Christakis, 2013. "Contagion of Cooperation in Static and Fluid Social Networks," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-10, June.
  • Handle: RePEc:plo:pone00:0066199
    DOI: 10.1371/journal.pone.0066199
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    2. Stojkoski, Viktor & Karbevski, Marko & Utkovski, Zoran & Basnarkov, Lasko & Kocarev, Ljupco, 2021. "Evolution of cooperation in networked heterogeneous fluctuating environments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    3. Syngjoo Choi & Edoardo Gallo & Shachar Kariv, 2015. "Networks in the laboratory," Cambridge Working Papers in Economics 1551, Faculty of Economics, University of Cambridge.
    4. Ahmadreza Asgharpourmasouleh & Atiye Sadeghi & Ali Yousofi, 2017. "A Grounded Agent-Based Model of Common Good Production in a Residential Complex: Applying Artificial Experiments," SAGE Open, , vol. 7(4), pages 21582440177, October.
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    6. Vasiliki Fouka & Soumyajit Mazumder & Marco Tabellini, 2018. "From Immigrants to Americans: Race and Assimilation during the Great Migration," Harvard Business School Working Papers 19-018, Harvard Business School, revised Jun 2019.
    7. Pei-Pei Liu & Vasiliy Safin & Barry Yang & Christian C Luhmann, 2015. "Direct and Indirect Influence of Altruistic Behavior in a Social Network," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-18, October.

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