From Caricature to Collective Artifact: How Persona Construction Drives Polarization in Generative Social Simulations
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...
| Authors | Dimitris Michailidis, Petter Törnberg, Fernando P. Santos |
|---|---|
| Primary category | cs.SI |
| Published | 12 October 2026 |
| Last updated at source | 12 October 2026 |
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