1 citations · 1 across the 7 of their papers we have counts for
7 papers
When Persona Attributes Improve Population Alignment in Large Language Models
Leon Fröhling, Jens Rupprecht, Markus Strohmaier +1
Large Language Models (LLMs) are increasingly used to predict the responses of human participants in survey panels. Towards that goal, persona prompting has recently emerged as a t…
Hybrid Panels: Toward Human-AI Collaboration in Survey Research
Julia Romberg, Tobias Gummer, Gabriella Lapesa +2
Large-scale population surveys are essential for generating robust social and scientific insights, yet they face significant challenges, including declining response rates, increas…
From Emotion to Expression: Theoretical Foundations and Resources for Fear Speech
Vigneshwaran Shankaran, Gabriella Lapesa, Claudia Wagner
Few forces rival fear in their ability to mobilize societies, distort communication, and reshape collective behavior. In computational linguistics, fear is primarily studied as an…
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…
Learning from Convenience Samples: Fine-Tuning LLMs to Predict Voting Choices from Biased Survey Samples
Tobias Holtdirk, Dennis Assenmacher, Arnim Bleier +1
Survey research increasingly relies on convenience samples as rising costs and nonresponse make representative probability sampling more difficult. This creates a central challenge…
Facts are Harder Than Opinions -- A Multilingual, Comparative Analysis of LLM-Based Fact-Checking Reliability
Lorraine Saju, Arnim Bleier, Jana Lasser +1
The proliferation of misinformation necessitates scalable, automated fact-checking solutions. Yet, current benchmarks often overlook multilingual and topical diversity. This paper…
Fair Pairs: Fairness-Aware Ranking Recovery from Pairwise Comparisons
Georg Ahnert, Antonio Ferrara, Claudia Wagner
Pairwise comparisons based on human judgements are an effective method for determining rankings of items or individuals. However, as human biases perpetuate from pairwise compariso…