Behavioral Conflict and Fairness in Social Networks

  • Stephen Judd
  • Michael Kearns
  • Yevgeniy Vorobeychik
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7090)


We report on a series of behavioral experiments in social networks in which human subjects continuously choose to play either a dominant role (called a King) or a submissive one (called a Pawn). Kings receive a higher payoff rate, but only if all their network neighbors are Pawns, and thus the maximum social welfare states correspond to maximum independent sets. We document that fairness is of vital importance in driving interactions between players. First, we find that payoff disparities between network neighbors gives rise to conflict, and the specifics depend on the network topology. However, allowing Kings to offer “tips” or side payments to their neighbors substantially reduces conflict, and consistently increases social welfare. Finally, we observe that tip reductions lead to increased conflict. We describe these and a broad set of related findings.


Social Welfare Preferential Attachment Repeated Game Ultimatum Game Income Disparity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Stephen Judd
    • 1
  • Michael Kearns
    • 1
  • Yevgeniy Vorobeychik
    • 2
  1. 1.Computer and Information ScienceUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.Sandia National LaboratoriesLivermoreUSA

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