Talk2AI: A Longitudinal Dataset of Human--AI Persuasive Conversations
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Abstract (arXiv)
Talk2AI is a large-scale longitudinal dataset of 3,080 conversations (totaling 30,800 turns) between human participants and Large Language Models (LLMs), designed to support research on persuasion, opinion change, and human-AI interaction. The corpus was collected from 770 profiled Italian adults across four weekly sessions in Spring 2025, using a within-subject design in which each participant conversed with a single model (GPT-4o, Claude Sonnet 3.7, DeepSeek-chat V3, or Mistral Large) on three socially relevant topics: climate change, math anxiety, and health misinformation. Each conversation is linked to rich contextual data, including sociodemographic characteristics and psychometric profiles. After each session, participants reported on opinion change, conviction stability, perceived humanness of the AI, and behavioral intentions, enabling fine-grained longitudinal analysis of how AI-mediated dialogue shapes beliefs and attitudes over time.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 6 of its 23 references that are in the map. First posted on arXiv 6 Apr 2026.
Builds on
6 of 23 references.
References · 6
- 2024GPT-4o System Cardcited by 4,588
- 2024On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trialcited by 109
- 2024Y Social: an LLM-powered Social Media Digital Twincited by 44
- 2024Large Language Models are as persuasive as humans, but how? About the cognitive effort and moral-emotional language of LLM argumentscited by 30
- 2025The Levers of Political Persuasion with Conversational AIcited by 20
- 2025Measuring and identifying factors of individuals' trust in Large Language Modelscited by 7
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Citing papers per year: 2026: 2.
2 papers.