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arXiv cs.AI· Dimitris Michailidis, Petter T\"ornberg, Fernando P. Santos·· 3 天前AI 评分31

从漫画到集体产物:人格构建如何驱动生成式社会模拟中的极化

From Caricature to Collective Artifact: How Persona Construction Drives Polarization in Generative Social Simulations

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研究基于类 Twitter 的生成式社会模拟平台,用 ANES 数据构建 LLM 智能体人格,并消融情感极化标记、党派认同与投票选择三层党派身份。结果显示,仅移除少数明确党派表述,网络就从近乎完全隔离转为接近真实 Twitter 的跨党联系。作者认为匹配单一结果不足以证明行为效度,并指出问卷对所有议题一视同仁、人格构建将每个回答变成直接行为指令,可能是关键原因。

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Abstract:Generative Social Simulation (GSS) leverages Large Language Models (LLMs) to create sophisticated personas that define agents with demographics, emotions, and political opinions. While prior work shows that personas compress outputs into stereotypical caricatures, there is no comprehensive study of how these caricatures evolve into collective artifacts when they interact. Using a Twitter-like GSS platform with personas derived from the American National Elections Study (ANES), we ablate three layers of partisan identity: affective polarization markers, party identification, and vote choice, while retaining demographics, ideological positioning and important issues. We find that collective outcomes depend heavily on how survey responses are translated into personas. Removing a few explicitly partisan statements moves the network from near-complete segregation to cross-party ties approaching those of real Twitter networks. We argue that matching one outcome is not evidence for behavioral validity and point to salience as a possible explanation. Surveys ask for a position on every question regardless of its importance to the respondent, and persona construction turns each answer into a direct behavioral instruction. We conclude with a checklist for more comprehensive evaluation of personas in future works.
Comments: 17 pages
Subjects: Social and Information Networks (cs.SI); Artificial Intelligence (cs.AI)
Cite as: arXiv:2610.16498 [cs.SI]
  (or arXiv:2610.16498v1 [cs.SI] for this version)
  https://doi.org/10.48550/arXiv.2610.16498

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Dimitris Michailidis [view email]
[v1] Mon, 12 Oct 2026 09:48:14 UTC (217 KB)

来源:arXiv cs.AI · arxiv.org