Talk2AI: A Longitudinal Dataset of Human--AI Persuasive Conversations
This dataset addresses the need for longitudinal data on human-AI persuasive interactions, supporting research in persuasion and opinion change, though it is incremental as it focuses on data collection rather than new methods.
The researchers tackled the problem of understanding how AI-mediated dialogue influences human beliefs and attitudes over time by creating Talk2AI, a large-scale longitudinal dataset of 3,080 conversations between humans and LLMs, which includes rich contextual data and post-session reports on opinion change and other metrics.
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.