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arXiv 2602.15064physics.soc-phcs.AI
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Moltbook中人工智能代理与人类社交网络的结构差异

Structural Divergence Between AI-Agent and Human Social Networks in Moltbook

Duke University School of Medicine(杜克大学医学学院)

Wenpin Hou, Zhicheng Ji

AI总结:

研究揭示了Moltbook中人工智能代理与人类社交网络在结构上的差异,显示AI代理社会能再现人类网络的全球结构规律,但内部组织原则不同。

摘要:

大规模的人工智能代理正越来越多地嵌入在线环境,但关于它们的集体互动模式与人类社交系统之间的比较仍知之甚少。在这里,我们分析了Moltbook平台的完整互动网络,该平台中人工智能代理和人类共存,并系统地将其结构与已充分表征的人类通信网络进行比较。尽管Moltbook遵循与人类系统观察到的相同节点-边缩放关系,表明具有可比的全球增长限制,但其内部组织却明显不同。该网络表现出极端的关注不平等,重尾且不对称的度分布,抑制的互惠性,以及连接三元结构的全球代表性不足。社区分析揭示出一种结构化的模块化架构,具有较高的模块度和相对较低的社区大小不平等程度,与保持度的空模型相比。这些发现表明,人工智能代理社会可以再现人类网络的全球结构规律,同时表现出根本不同的内部组织原则,强调人类社交组织的关键特征并非普遍,而是取决于相互作用代理的性质。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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