publications

2025

1. 

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

   Jens Rupprecht, Leon Fröhling, Claudia Wagner, and 1 more author

   Nov 2025

   arXiv:2511.21722 [cs]

   Abs DOI PDF

   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 Personas (GGP) collection, a comprehensive and representative persona prompt collection built from the German General Social Survey (ALLBUS). The GGP and its 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 GGP by prompting various LLMs to simulate survey response distributions across diverse topics, demonstrating that GGP-guided LLMs outperform state-of-the-art classifiers, particularly under data scarcity. Furthermore, we analyze how the representativity and attribute selection within persona prompts affect alignment with population responses. Our findings suggest that GGP provides a potentially valuable resource for research on LLM-based social simulations that enables more systematic explorations of population-aligned persona prompting in NLP and social science research.

2. 

   Prompt Perturbations Reveal Human-Like Biases in LLM Survey Responses

   Jens Rupprecht, Georg Ahnert, and Markus Strohmaier

   Jul 2025

   Abs DOI PDF

   Large Language Models (LLMs) are increasingly used as proxies for human subjects in social science surveys, but their reliability and susceptibility to known response biases are poorly understood. This paper investigates the response robustness of LLMs in normative survey contexts – we test nine diverse LLMs on questions from the World Values Survey (WVS), applying a comprehensive set of 11 perturbations to both question phrasing and answer option structure, resulting in over 167,000 simulated interviews. In doing so, we not only reveal LLMs’ vulnerabilities to perturbations but also reveal that all tested models exhibit a consistent }textit{recency bias} varying in intensity, disproportionately favoring the last-presented answer option. While larger models are generally more robust, all models remain sensitive to semantic variations like paraphrasing and to combined perturbations. By applying a set of perturbations, we reveal that LLMs partially align with survey response biases identified in humans. This underscores the critical importance of prompt design and robustness testing when using LLMs to generate synthetic survey data.

2023

1. 

   Schnellladen in der Stadt 1

   Felix Röckle, Carolin Heer, and Jens Rupprecht

   Jul 2023

   Abs DOI PDF

   Im Kontext des Markthochlaufs batterieelektrischer Pkw wird oft das Thema Ladeinfrastruktur diskutiert und dabei insbesondere die Frage aufgeworfen, wo und wie Personen ohne privaten Stellplatz zukünftig ein Elektroauto aufladen könnten. Eine mögliche Lösung für die Problemstellung sind urbane Schnellladeparks, dedizierte Parkplätze im städtischen Raum, die über mehrere, meist 4-6 Schnellladestationen mit 8-12 Ladepunkten für Elektrofahrzeuge verfügen. Das vorliegende Whitepaper legt dar, inwiefern diese Lademöglichkeit aus Nutzendensicht tatsächlich attraktiv ist, wie urbane Schnellladeparks heute genutzt werden und welche Anforderungen sie erfüllen müssen, um die Akzeptanz batterieelektrischer Fahrzeuge in Zukunft weiter zu erhöhen.

2022

1. 

   "Charging Process Chain"

   Felix Röckle, Marco Raul Soares Amorim, Lukas Keicher, and 2 more authors

   Jul 2022

   Abs DOI PDF

   As part of the "Wirkkette Laden" funding project, a holistic approach for analysing weak points in the charging ecosystem was developed and applied in collaboration between research and industry. The approach is based on four building blocks: Statistical data analysis, a diary study, a charging experiment, and an AI-based analysis of online user comments. The results show that there are challenges both in terms of the individual components of the charging ecosystem, such as charging stations, and in terms of the interfaces between the components within the system.