9 papers
Survey Response Generation: Generating Closed-Ended Survey Responses In-Silico with Large Language Models
Georg Ahnert, Anna-Carolina Haensch, Barbara Plank +1
Many in-silico simulations of human survey responses with large language models (LLMs) focus on generating closed-ended survey responses, whereas LLMs are typically trained to gene…
German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies
Jens Rupprecht, Leon Fröhling, Claudia Wagner +1
The use of Large Language Models (LLMs) for simulating human perspectives via persona prompting is gaining traction in computational social science. However, well-curated, empirica…
QSTN: A Modular Framework for Robust Questionnaire Inference with Large Language Models
Maximilian Kreutner, Jens Rupprecht, Georg Ahnert +2
We introduce QSTN, an open-source Python framework for systematically generating responses from questionnaire-style prompts to support in-silico surveys and annotation tasks with l…
Neural network embeddings recover value dimensions from psychometric survey items on par with human data
Max Pellert, Clemens M. Lechner, Indira Sen +1
We demonstrate that embeddings derived from large language models, when processed with "Survey and Questionnaire Item Embeddings Differentials" (SQuID), can recover the structure o…
Prompt Perturbations Reveal Human-Like Biases in Large Language Model Survey Responses
Jens Rupprecht, Georg Ahnert, Markus Strohmaier
Large Language Models (LLMs) are increasingly used as proxies for human subjects in social science surveys, but their reliability and susceptibility to known human-like response bi…
Simulating Persuasive Dialogues on Meat Reduction with Generative Agents
Georg Ahnert, Elena Wurth, Markus Strohmaier +1
Meat reduction benefits human and planetary health, but social norms keep meat central in shared meals. To date, the development of communication strategies that promote meat reduc…