Discover 8 peer-reviewed studies in Political Science (2022–2026). Explore research findings powered by Prolific's diverse participant panel.
This page lists 8 peer-reviewed papers in the research area of Political Science in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.
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Authors: C Yuan, B Ma, Z Zhang, B Prenkaj, F Kreuter, G Kasneci
Year: 2026
Published in: arXiv preprint arXiv:2601.08634, 2026•arxiv.org
Institution: Munich Center for Machine Learning, LMU Munich, Technical University of Munich
Research Area: Artificial Intelligence, AI Ethics, AI Alignment, Political Science, Computational Social Science
Discipline: Computer Science, Natural Language Processing (NLP)
This paper examines how large language models’ (LLMs) political outputs shift when you explicitly prime them with different moral values. Instead of just assigning fake personas (like “pretend to be liberal”), the authors condition models to endorse or reject specific moral values (e.g., utilitarianism, fairness, authority). They then measure how those moral primes move the models’ positions in...
DOI: https://doi.org/10.48550/arXiv.2601.08634
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Authors: N Aldahoul, H Ibrahim, M Varvello, A Kaufman
Year: 2025
Published in: arXiv preprint arXiv ..., 2025 - arxiv.org
Institution: Delft University of Technology, University of Pennsylvania, New York University, King Abdullah University of Science and Technology, Massachusetts Institute of Technology, University of Texas at Austin
Research Area: Artificial Intelligence, Computers and Society, Political Science
Discipline: Artificial Intelligence, Social Science
The study finds that Large Language Models (LLMs) exhibit extreme political views on specific topics despite appearing ideologically moderate overall, and demonstrate a persuasive influence on users' political preferences even in informational contexts.
Methods: Compared 31 LLMs' political biases against benchmarks (legislators, judges, representative voter samples) and conducted a randomized experiment to measure their persuasive impact in informational interactions.
Key Findings: Ideological consistency, political extremity, and persuasive effects of LLMs in information-seeking contexts.
Citations: 7
Sample Size: 31
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Authors: H Shakeeb, C Conrad
Year: 2025
Published in: 2025 - aisel.aisnet.org
Institution: Dalhousie University
Research Area: AI, Political Communication, Media Trustworthiness, Cognitive Science, Autonomous Applications
Discipline: Artificial Intelligence, Cognitive Science
AI-generated audio in political communication is perceived as more trustworthy than image or video formats, but lower realism leads to skepticism.
Methods: An online experiment with participants assessing AI-generated political content in audio, video, and image formats; data analyzed using linear mixed effects analysis and NLP.
Key Findings: Impact of AI-generated media formats on trust and willingness to follow political recommendations, considering realism levels.
Citations: 1
Sample Size: 150
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Authors: A Simchon, M Edwards, S Lewandowsky
Year: 2024
Published in: PNAS nexus, 2024 - academic.oup.com
Institution: University of Bristol
Research Area: Political Microtargeting, Generative AI, Political Science, Psychological and Cognitive Sciences
Discipline: Political Science, Psychology
The study highlights the effectiveness and scalability of using generative AI to microtarget personalized political advertisements based on personality traits, raising ethical and policy concerns.
Methods: Four studies were conducted, including experiments (studies 1a and 1b) on the effectiveness of personality-tailored ads and feasibility assessments (studies 2a and 2b) of automatic generation and validation of these ads using generative AI and personality inference.
Key Findings: Effectiveness of personality-based microtargeted political ads and the scalability of their generation using generative AI tools.
Citations: 172
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Authors: K Hackenburg, BM Tappin, P Röttger, S Hale
Year: 2024
Published in: arXiv preprint arXiv ..., 2024 - arxiv.org
Institution: University of Oxford, The Alan Turing Institute, Royal Holloway, University of London, Bocconi University, Meedan
Research Area: LLM scaling laws, Political Persuasion, LLM, AI Social Science
Discipline: Political Science, Artificial Intelligence
Persuasiveness of messages generated by large language models follows a log scaling law with diminishing returns as model size increases, and task completion appears to primarily drive this capability.
Methods: Generated 720 persuasive messages on 10 U.S. political issues using 24 language models of varying sizes; evaluated persuasiveness through a large-scale randomized survey experiment.
Key Findings: Persuasiveness of large language model-generated political messages across different model sizes.
Citations: 17
Sample Size: 25982
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Authors: K Hackenburg, H Margetts
Year: 2023
Published in: Proceedings of the National Academy of ..., 2024 - pnas.org
Institution: Oxford University, Alan Turing Institute
Research Area: Political Persuasion, LLM, Political Science
Discipline: Political Science
DOI: https://doi.org/10.1073/pnas.2403116121
Citations: 153
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Authors: H Bai, J Voelkel, J Eichstaedt, R Willer
Year: 2023
Published in: 2023 - researchsquare.com
Institution: Stanford University, London Business School, Dartmouth College, Stanford Graduate School of Business
Research Area: Political Persuasion, Social Influence of AI, Cognitive Science
Discipline: Political Science, Social Science
Citations: 100
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Authors: M Chung, J Wihbey
Year: 2022
Published in: New Media & Society, 2024 - journals.sagepub.com
Research Area: Communication and Media Studies, Political Science, or International Relations (Comparative Studies)
Discipline: Social Sciences, Humanities
DOI: https://doi.org/10.1177/14614448221122996
Citations: 24