Authors: K Hackenburg, BM Tappin, P Röttger, SA Hale
Year: 2025
Published in: Proceedings of the ..., 2025 - pnas.org
Institution: University of California Berkeley, University of Cambridge, University of Oxford, Max Planck Institute
Research Area: Political Persuasion, LLM
Discipline: Computational Social Science, Political Science
Scaling language model sizes leads to diminishing returns in generating persuasive political messages, with larger models providing minimal gains compared to smaller ones after controlling for task completion metrics like coherence and relevance.
Methods: Generated 720 political messages using 24 LLMs of varying sizes and tested their persuasiveness through a large-scale randomized survey experiment.
Key Findings: Persuasive capability of language models across different sizes in generating political messages.
Citations: 31
Sample Size: 25982