[2511.21722] German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies

Computer Science > Computation and Language arXiv:2511.21722 (cs) [Submitted on 19 Nov 2025 (v1), last revised 2 Mar 2026 (this version, v2)] Title:German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies Authors:Jens Rupprecht, Leon Fröhling, Claudia Wagner, Markus Strohmaier View a PDF of the paper titled German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies, by Jens Rupprecht and 3 other authors View PDF HTML (experimental) Abstract:The use of Large Language Models (LLMs) for simulating human perspectives via persona prompting is gaining traction in computational social science. However, well-curated, empirically grounded persona collections remain scarce, limiting the accuracy and representativeness of such simulations. Here, we introduce the German General Social Survey Personas (GGSS Personas) collection, a comprehensive and representative persona prompt collection built from the German General Social Survey (ALLBUS). The GGSS Personas and their persona prompts are designed to be easily plugged into prompts for all types of LLMs and tasks, steering models to generate responses aligned with the underlying German population. We evaluate GGSS Personas by prompting various LLMs to simulate survey response distributions across diverse topics, demonstrating that GGSS Personas-guided LLMs outperform state-of-the-art classifiers, particularly under data ...