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Cooperation in Evolving Social Networks

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Author Info

  • Nobuyuki Hanaki

    () (Doctoral Program in International Political Economy, Graduate School of Humanity and Social Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan)

  • Alexander Peterhansl

    () (Department of Economics, Columbia University, 1022 International Affairs Building, 420 West 118th Street, New York, New York 10027)

  • Peter S. Dodds

    () (Department of Mathematics and Statistics, 203 Lord House, University of Vermont, 16 Colchester Avenue, Burlington, Vermont 05401)

  • Duncan J. Watts

    () (Institute for Social and Economic Research and Policy, Columbia University, 8th Floor, International Affairs Building, 420 West 118th Street, New York, New York 10027 and Department of Sociology, Columbia University, 413 Fayerweather Hall, 1180 Amsterdam Avenue, New York, New York 10027)

Abstract

We study the problem of cooperative behavior emerging in an environment where individual behaviors and interaction structures coevolve. Players not only learn which strategy to adopt by imitating the strategy of the best-performing player they observe, but also choose with whom they should interact by selectively creating and/or severing ties with other players based on a myopic cost-benefit comparison. We find that scalable cooperation--that is, high levels of cooperation in large populations--can be achieved in sparse networks, assuming that individuals are able to sever ties unilaterally and that new ties can only be created with the mutual consent of both parties. Detailed examination shows that there is an important trade-off between local reinforcement and global expansion in achieving cooperation in dynamic networks. As a result, networks in which ties are costly and local structure is largely absent tend to generate higher levels of cooperation than those in which ties are made easily and friends of friends interact with high probability, where the latter result contrasts strongly with the usual intuition.

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File URL: http://dx.doi.org/10.1287/mnsc.1060.0625
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Bibliographic Info

Article provided by INFORMS in its journal Management Science.

Volume (Year): 53 (2007)
Issue (Month): 7 (July)
Pages: 1036-1050

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Handle: RePEc:inm:ormnsc:v:53:y:2007:i:7:p:1036-1050

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Related research

Keywords: networks-graphs; theory; games-group decisions; simulation;

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Cited by:
  1. Haydée Lugo & Raúl Jiménez, 2006. "Incentives to Cooperate in Network Formation," Computational Economics, Society for Computational Economics, vol. 28(1), pages 15-27, August.
  2. Mengel, Friederike & Fosco, Constanza, 2007. "Cooperation through Imitation and Exclusion in Networks," MPRA Paper 5258, University Library of Munich, Germany.
  3. Faqi Du & Feng Fu, 2011. "Partner Selection Shapes the Strategic and Topological Evolution of Cooperation," Dynamic Games and Applications, Springer, vol. 1(3), pages 354-369, September.
  4. Constanza Fosco & Matteo Marsili & Fernando Vega-Redondo, 2008. "Peer Effects and Peer Avoidance: Epidemic Diffusion in Coevolving Networks," Economics Working Papers ECO2008/19, European University Institute.
  5. Jason Barr & Troy Tassier, 2010. "Endogenous Neighborhood Selection and the Attainment of Cooperation in a Spatial Prisoner’s Dilemma Game," Computational Economics, Society for Computational Economics, vol. 35(3), pages 211-234, March.
  6. Edoardo Mollona, 2008. "Computer simulation in social sciences," Journal of Management and Governance, Springer, vol. 12(2), pages 205-211, May.
  7. Mengel, Friederike, 2007. "Conformism and Cooperation in a Local Interaction Model," MPRA Paper 4051, University Library of Munich, Germany.
  8. Julian Dormann & Thomas Ehrmann & Michael Kopel, 2008. "Managing the Evolution of Cooperation," Papers on Economics and Evolution 2008-01, Max Planck Institute of Economics, Evolutionary Economics Group.

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