Talk2AI: A Longitudinal Dataset of Human--AI Persuasive Conversations

TL;DR

Talk2AI is a comprehensive longitudinal dataset of human-AI persuasive conversations involving 770 Italian adults, enabling research on opinion change and human-AI interaction over multiple sessions.

Contribution

It introduces a large-scale, longitudinal dataset linking detailed conversational data with sociodemographic and psychometric profiles for studying persuasion.

Findings

Rich contextual data linked to each conversation.

Participants reported on opinion change and perceived AI humanness.

Dataset supports analysis of belief and attitude shifts over time.

Abstract

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.