收集3000+轮人机对话，研究AI如何影响人们观点变化。
Talk2AI: A Longitudinal Dataset of Human--AI Persuasive Conversations
- 通过每周对话实验，追踪4类大模型对用户观点的影响。
- 每轮对话后评估观点改变、信念稳定性及对AI的感知真实度。
- 适合研究人机交互、说服力与社会议题认知的学者参考。
Talk2AI 是一个大规模纵向数据集，包含3,080次对话（共30,800轮），由770名意大利成年人在2025年春季分四周完成，每位参与者与单一大语言模型（GPT-4o、Claude Sonnet 3.7、DeepSeek-chat V3或Mistral Large）就气候变化、数学焦虑和健康错误信息三个社会议题展开对话。采用被试内设计，每轮对话后参与者报告观点改变、信念稳定性、对AI的人性感知及行为意向，附带丰富的社会人口学与心理测量特征数据，支持对人机对话如何随时间塑造态度与信念的精细分析。
原文摘要 · Abstract (English)
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.
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