标题： 分形社会动力学作为共识与不平等的驱动因素 显示英文标题

标题： Fractal Social Dynamics as a Driver of Consensus and Inequality

摘要： 人类社会行为组织在分层的、等级化的网络中，有一个大约5人的支持群体，每一层按比例扩展，最多达到每个个体约150次频繁互动。 这被称为社会大脑假说，其研究结果得到了心理学和神经学证据的支持。 分形网络框架为诸如虚假新闻传播和技术发展等社会现象提供了有价值的见解。 本研究使用分形网络对经济社会互动进行建模，其中群体规模按固定因子扩展，以分析共识是如何形成的。 使用$q$-微积分，该模型揭示了层次结构如何影响信息传播，突出了由幂律支配的普遍特征。 结果遵循$q$-高斯分布，显示出与全球社会中观察到的不平等相一致的重尾特性。 结果表明，不平等来自于经济社会网络的分形结构。 显示英文摘要

摘要： Human social behavior is organized in stratified, hierarchical networks, with a support group with about 5 members, expanding proportionally at each layer up to a maximum of approximately 150 frequent interactions per individual. This is known as Social Brain Hypothesis, and its findings are supported by psychological and neurological evidence. The fractal network framework provides valuable insights into social phenomena such as the spread of fake news and the development of technology. This study models socioeconomic interactions using fractal networks, where group sizes scale by a fixed factor, to analyze how consensus is formed. Using $q$-calculus, the model reveals how hierarchical structures influence information spread, highlighting universal features governed by power laws.. The results follow $q$-Gaussian distributions, showing heavy-tails that align with observed inequalities in societies worldwide. The results show that inequalities arise from the fractal structure of the socioeconomic network.