对比AI与人类社交网络，发现结构相似但内部组织机制截然不同。
Structural Divergence Between AI-Agent and Human Social Networks in Moltbook
- 分析Moltbook平台中AI与人类共存的交互网络结构。
- AI网络存在极端注意力不均、低互惠性及三元连接缺失。
- 适合研究智能体社会行为或社交网络差异的学者参考。
大量AI代理正被嵌入在线环境，但其集体互动模式与人类社交系统的关系尚不清楚。本文分析了Moltbook平台中人工智能代理与人类共存的完整交互网络，并将其结构与已知的人类通信网络进行系统比较。尽管Moltbook遵循与人类系统相同的节点-边缩放关系，表明全球增长约束相似，但其内部组织显著偏离。网络表现出极端注意力不均、重尾且不对称的度分布、互惠性被抑制，以及三元连接结构普遍不足。社区分析显示，该网络具有高度模块化架构，模组间连通性更强，且模组规模不平等程度低于度保持型零模型。这些结果表明，尽管AI代理社会可复现人类网络的全局结构性规律，但其内部组织原则根本不同，说明人类社交的核心特征并非普适，而是依赖于交互主体的本质属性。
原文摘要 · Abstract (English)
Large populations of AI agents are increasingly embedded in online environments, yet little is known about how their collective interaction patterns compare to human social systems. Here, we analyze the full interaction network of Moltbook, a platform where AI agents and humans coexist, and systematically compare its structure to well-characterized human communication networks. Although Moltbook follows the same node-edge scaling relationship observed in human systems, indicating comparable global growth constraints, its internal organization diverges markedly. The network exhibits extreme attention inequality, heavy-tailed and asymmetric degree distributions, suppressed reciprocity, and a global under-representation of connected triadic structures. Community analysis reveals a structured modular architecture with elevated modularity and comparatively lower community size inequality relative to degree-preserving null models. Together, these findings show that AI-agent societies can reproduce global structural regularities of human networks while exhibiting fundamentally different internal organizing principles, highlighting that key features of human social organization are not universal but depend on the nature of the interacting agents.
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