Bm Tappin: Researcher — Prolific Citations Library

Explore 4 peer-reviewed studies by Bm Tappin in LLM and Political Persuasion (2024–2025). Discover research powered by Prolific's participant panel.

This page lists 4 peer-reviewed papers authored or co-authored by Bm Tappin in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (4 of 4)

Comparing the persuasiveness of role-playing large language models and human experts on polarized US political issues

Authors: K Hackenburg, L Ibrahim, BM Tappin, M Tsakiris

Year: 2025

Published in: AI & SOCIETY, 2025 - Springer

Institution: Oxford Internet Institute, University of Oxford

Research Area: Political Communication and Persuasion, LLM

Discipline: Political Science, Artificial Intelligence

GPT-4's ability to generate persuasive messages rivaled human experts on polarized US political issues, suggesting AI tools may have significant implications for political campaigns and democracy.

Methods: Pre-registered experiment where GPT-4 generated partisan role-playing persuasive messages, which were compared to those from human persuasion experts.

Key Findings: Persuasive impact of GPT-4-generated messages versus human expert messages on U.S. political issues.

Citations: 35

Sample Size: 4955
Scaling language model size yields diminishing returns for single-message political persuasion

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
The levers of political persuasion with conversational artificial intelligence

Authors: K Hackenburg, BM Tappin, L Hewitt, E Saunders

Year: 2025

Published in: Science, 2025 - science.org

Institution: London School of Economics and Political Science, Stony Brook University

Research Area: Political Persuasion with Conversational AI, LLM, Factual Accuracy in AI Systems.

Discipline: Political Science, Computational Social Science

This Science paper shows that conversational AI chatbots can systematically influence political opinions at scale, and that techniques like post-training and prompting make them far more persuasive—but that increased persuasion is tied to reduced factual accuracy in what the AI says.

Citations: 12
Evidence of a log scaling law for political persuasion with large language models

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