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Quality versus quantity of social ties in experimental cooperative networks

Author

Listed:
  • Hirokazu Shirado

    (Corporate R&D, Sony Corporation, Shinagawa
    Harvard Medical School)

  • Feng Fu

    (Harvard Medical School
    Program for Evolutionary Dynamics, Harvard University
    Present address: Theoretical Biology Group, Institute of Integrative Biology, ETH Zurich, Zurich, 8092, Switzerland)

  • James H. Fowler

    (University of California-San Diego
    University of California-San Diego)

  • Nicholas A. Christakis

    (Yale University
    Yale University
    Yale Institute of Network Science, Yale University, PO Box 208263, New Haven, Connecticut 06520, USA)

Abstract

Recent studies suggest that allowing individuals to choose their partners can help to maintain cooperation in human social networks; this behaviour can supplement behavioural reciprocity, whereby humans are influenced to cooperate by peer pressure. However, it is unknown how the rate of forming and breaking social ties affects our capacity to cooperate. Here we use a series of online experiments involving 1,529 unique participants embedded in 90 experimental networks, to show that there is a ‘Goldilocks’ effect of network dynamism on cooperation. When the rate of change in social ties is too low, subjects choose to have many ties, even if they attach to defectors. When the rate is too high, cooperators cannot detach from defectors as much as defectors re-attach and, hence, subjects resort to behavioural reciprocity and switch their behaviour to defection. Optimal levels of cooperation are achieved at intermediate levels of change in social ties.

Suggested Citation

  • Hirokazu Shirado & Feng Fu & James H. Fowler & Nicholas A. Christakis, 2013. "Quality versus quantity of social ties in experimental cooperative networks," Nature Communications, Nature, vol. 4(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:4:y:2013:i:1:d:10.1038_ncomms3814
    DOI: 10.1038/ncomms3814
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    Cited by:

    1. Gallo, Edoardo & Riyanto, Yohanes E. & Roy, Nilanjan & Teh, Tat-How, 2019. "Cooperation in an Uncertain and Dynamic World," MPRA Paper 97878, University Library of Munich, Germany.
    2. Brent Simpson & Bradley Montgomery & David Melamed, 2023. "Reputations for treatment of outgroup members can prevent the emergence of political segregation in cooperative networks," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    3. Edoardo Gallo & Yohanes E. Riyanto & Nilanjan Roy & Tat-How Teh, 2022. "Cooperation and punishment mechanisms in uncertain and dynamic networks," Papers 2203.04001, arXiv.org.
    4. Kevin R. McKee & Andrea Tacchetti & Michiel A. Bakker & Jan Balaguer & Lucy Campbell-Gillingham & Richard Everett & Matthew Botvinick, 2023. "Scaffolding cooperation in human groups with deep reinforcement learning," Nature Human Behaviour, Nature, vol. 7(10), pages 1787-1796, October.
    5. Hirofumi Takesue, 2020. "From defection to ingroup favoritism to cooperation: simulation analysis of the social dilemma in dynamic networks," Journal of Computational Social Science, Springer, vol. 3(1), pages 189-207, April.
    6. Gallo, Edoardo & Riyanto, Yohanes E. & Roy, Nilanjan & Teh, Tat-How, 2022. "Cooperation and punishment mechanisms in uncertain and dynamic social networks," Games and Economic Behavior, Elsevier, vol. 134(C), pages 75-103.
    7. Takahiro Ezaki & Naoki Masuda, 2017. "Reinforcement learning account of network reciprocity," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-8, December.
    8. Riyanto, Yohanes E. & Teh, Tat-How, 2020. "Highly flexible neighborhood promotes efficient coordination: Experimental evidence," European Economic Review, Elsevier, vol. 129(C).
    9. Zheng, Junjun & He, Yujie & Ren, Tianyu & Huang, Yongchao, 2022. "Evolution of cooperation in public goods games with segregated networks and periodic invasion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    10. Jiang, Zhi-Qiang & Wang, Peng & Ma, Jun-Chao & Zhu, Peican & Han, Zhen & Podobnik, Boris & Stanley, H. Eugene & Zhou, Wei-Xing & Alfaro-Bittner, Karin & Boccaletti, Stefano, 2023. "Unraveling the effects of network, direct and indirect reciprocity in online societies," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    11. Edoardo Gallo & Joseph Lee & Yohanes Eko Riyanto & Erwin Wong, 2023. "Cooperation and Cognition in Social Networks," Papers 2305.01209, arXiv.org.
    12. Takesue, Hirofumi, 2021. "Symmetry breaking in the prisoner’s dilemma on two-layer dynamic multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 388(C).

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