Abstract

Recently there has been an increased interest in adopting game-theoretic models to social norms. Most of these approaches are generally lacking a structure linking the local level of the ‘norm’ interaction to its global ‘social’ nature. Although numerous studies examined local-interaction games, where the emphasis is placed on neighborhood relations, regarding social network as a whole unique entity seems to be quite limited. In this paper, we conduct a series of simulation experiments to examine the effects that a network topology could have on the speed of emergence of the social norm. The emphasis is placed on the fairness norm in the ultimatum game context, by considering three network type models (Barabási–Albert, Watts–Strogatz and Erdős–Rényi) and several intrinsic topological properties.

Highlights

  • Social norms (SN) are customary rules of behaviors that coordinate people’s interactions with each others, as defined by Young in [10]

  • In order to study the fairness norm, which is central to human coordination, we focus on the ultimatum game, but in a more realistic outlook accounting for the social network connection

  • This paper is about the emergence of Social Norms (SN) in a social network structure

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Summary

Introduction

Social norms (SN) are customary rules of behaviors that coordinate people’s interactions with each others, as defined by Young in [10] They are different from mere conventions and fashions; they could guide our collective behaviors in social situations, even at the expense of our individual interest [2]. We focus on the game-theoretic approaches to SN, given that an increasing number of related studies have been reported in recent years [22]. In this setting, a SN is primarily perceived as a Nash equilibrium of a symmetric game with multiple equilibria, usually a coordination game. Two expectations for conditional preferences are specified: empirical expectation, where the individual believes

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