Validating LLM-generated political networks with survey-reported partisan exposure
Large language models (LLMs) are increasingly used to simulate human behavior in social science research, including decisions, interactions, and social relationships. However, in network formation tasks, existing evaluations often focus on aggregate network properties, while networks with plausible structural properties may still fail to reproduce individuals' social and political environments. Here, we generate LLM-based political networks using personas sampled from the nationally representative ANES 2020--2022 Social Media Study and use respondents' survey-reported partisan exposure as an empirical benchmark for the political environments generated for the corresponding personas. We fi...
| Authors | Marco Tonin, Michele Tizzoni, Bruno Lepri et al. |
|---|---|
| Primary category | cs.SI |
| Published | 16 October 2026 |
| Last updated at source | 16 October 2026 |
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