How Persuasive Could LLMs Be? A First Study Combining Linguistic-Rhetorical Analysis and User Experiments
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Abstract (arXiv)
This study examines the rhetorical and linguistic features of argumentative texts generated by ChatGPT on ethically nuanced topics and investigates their persuasive impact on human readers.Through a user study involving 62 participants and pre-post interaction surveys, the paper analyzes how exposure to AI-generated arguments affects opinion change and user perception. A linguistic and rhetorical analysis of the generated texts reveals a consistent argumentative macrostructure, reliance on formulaic expressions, and limited stylistic richness. While ChatGPT demonstrates proficiency in constructing coherent argumentative texts, its persuasive efficacy appears constrained, particularly on topics involving ethical issues.The study finds that while participants often acknowledge the benefits highlighted by ChatGPT, ethical concerns tend to persist or even intensify post-interaction. The results also demonstrate a variation depending on the topic. These findings highlight new insights on AI-generated persuasion in ethically sensitive domains and are a basis for future research.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 15 of its 32 references that are in the map. First posted on arXiv 13 Aug 2025.
Builds on
15 of 32 references.
References · 15
- 2023The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Textcited by 100
- 2024Hidden Persuaders: LLMs' Political Leaning and Their Influence on Voterscited by 71
- 2023Contrasting Linguistic Patterns in Human and LLM-Generated News Textcited by 62
- 2023What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variabilitycited by 51
- 2025The Widespread Adoption of Large Language Model-Assisted Writing Across Societycited by 51
- 2024Standardizing the Measurement of Text Diversity: A Tool and a Comparative Analysis of Scorescited by 50
- 2023Machine-Made Media: Monitoring the Mobilization of Machine-Generated Articles on Misinformation and Mainstream News Websitescited by 38
- 2024A Shocking Amount of the Web is Machine Translated: Insights from Multi-Way Parallelismcited by 35
- 2024Are We in the AI-Generated Text World Already? Quantifying and Monitoring AIGT on Social Mediacited by 35
- 2024Persuasion with Large Language Models: A Survey of Empirical Evidence, Study Methodologies, and Ethical Implicationscited by 32
- 2024Large Language Models are as persuasive as humans, but how? About the cognitive effort and moral-emotional language of LLM argumentscited by 30
- 2025Human Decision-making is Susceptible to AI-driven Manipulationcited by 19
3 more
- 2024Large Language Models as Instruments of Power: New Regimes of Autonomous Manipulation and Controlcited by 10
- 2025The Dead Internet Theory: A Survey on Artificial Interactions and the Future of Social Mediacited by 3
- 2025Cyri: A Conversational AI-based Assistant for Supporting the Human User in Detecting and Responding to Phishing Attackscited by 1
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Citing papers per year: 2026: 1.
1 paper.