社会动态、信任和经济绩效的代际重叠模型中小世界网络的出现

Katarzyna Growiec, J. Growiec, B. Kamiński
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引用次数: 0

摘要

我们研究了人工社会中社会关系的内生建立和破坏对总体结果(如普遍信任、合作意愿、社会效用和经济绩效)的影响。为此,我们提出了一种计算型多智能体模型,其中重叠代的智能体在动态进化的社会网络中相互作用。在该模型中,个体社会资本的四个不同维度:程度、中心性、异性互动和同性互动,决定了他们的普遍信任和合作意愿,共同帮助他们实现一定水平的社会效用(即社会联系的效用)和经济绩效。我们发现所模拟的社会网络的定态呈现出真实的小世界拓扑结构。我们还观察到,社会网络相对频繁重构的社会,以较低的社会效用为代价,表现出相对较高的普遍信任、合作意愿和经济绩效。类似的结果也出现在社会关系破裂与家庭亲密关系相对较弱的社会中。
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Emergence of Small-World Networks in an Overlapping-Generations Model of Social Dynamics, Trust and Economic Performance
We study the impact of endogenous creation and destruction of social ties in an artificial society on aggregate outcomes such as generalized trust, willingness to cooperate, social utility and economic performance. To this end we put forward a computational multi-agent model where agents of overlapping generations interact in adynamically evolving social network. In themodel, four distinct dimensionsof individuals’ social capital: degree, centrality, heterophilous and homophilous interactions, determine their generalized trust and willingness to cooperate, altogether helping them achieve certain levels of social utility (i.e., utility from social contacts) and economic performance. We find that the stationary state of the simulated social network exhibits realistic small-world topology. We also observe that societies whose social networks are relatively frequently reconfigured, display relativelyhighergeneralized trust,willingness tocooperate, andeconomicperformance— at the cost of lower social utility. Similar outcomes are found for societies where social tie dissolution is relatively weakly linked to family closeness.
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