The Social Honesty game - A computational analysis of the impact of conformity and identity on honest behavior contagion in complex social systems

Abstract

Abstract We consider a probabilistic-payoff social dilemma game and we analyze the impact of various social learning mechanisms - conformity, diversity generators, identity, on the dynamics of honest behavior in a virtual population. To capture the inherent variability and uncertainty of a complex social environment, the proposed model considers probabilistic payoffs as well as a variety of strategy updating rules and hybrid neighborhood topologies. The implicit underlying mechanisms are those of imitation and social influence. By simulating evolutionary spatial scenarios, we identify factors that favor contagion of honest behavior (i.e. social honesty) in the context of probabilistic payoff. Conformity and identity have a significant effect on the contagion of honest behavior. They slow down the dynamics, make it more stable, and help the formation and growth of clusters, favoring the emergence and spreading of honest behavior. However, their impact is topology dependent, nonlinear, exhibiting phase shifts. High conformity favors honest behavior in simple topologies, and does the opposite in complex topologies. Without a certain degree of diversity (use of alternative strategies) the system loses its adaptation capability. At the other end, strategy inconsistency leads to chaos, which favors the contagion of dishonest behavior. A structuring effect of leaders on chaotic behavior is also observed: their presence reduces the effects of random behavior, inducing alignment and reducing the necessity of a higher punishment probability. The key findings of this research can help predict trends and design public and organizational policies to nudge honest behavior, in the context of high complexity dynamics generated by the recent advances in information technology.