Authors: Z Chen, J Kalla, Q Le, S Nakamura-Sakai
Year: 2025
Published in: arXiv preprint arXiv ..., 2025 - arxiv.org
Institution: The affiliated institutions could not be determined from the provided context or an external search of the URL.
Research Area: Artificial Intelligence and Social Science, Persuasion Studies, Political Persuasion, LLM Chatbots, Democratic Societies
Discipline: Artificial Intelligence, Social Science
The study evaluates the cost-effectiveness and persuasive risks of Large Language Model (LLM) chatbots in political contexts, finding that while LLMs are as persuasive as campaign ads under exposure, their large-scale influence is currently limited by scalability and cost barriers.
Methods: Two survey experiments combined with real-world simulation exercises to measure the persuasiveness of LLM chatbots compared to traditional campaign tactics, focusing on both exposure and acceptance phases of persuasion.
Key Findings: Short- and long-term persuasive effects of LLMs, cost-effectiveness of LLM-based persuasion ($48-$74 per persuaded voter), and scalability compared to traditional campaign approaches.
Citations: 7
Sample Size: 10417
