Dataset of Annotated X (Twitter) Misinformation Posts with Human and Large Language Model (LLM) Responses for Cognitive Analysis

We provide a dataset which can help researchers to conduct cognitive analysis on social media posts such as: study how individuals perceive, interpret and react to online posts. Cognitive analysis of LLMs not only analyse user metrics and binary misinformation labels but it also aims to uncover the underlying reasoning patterns, attitudes, and biases that shape social media behaviour. This perspective is crucial for understanding why certain misinformation narratives gain virality, how beliefs evolve, and what influences user trust or disbelief in online content.

本数据集可供研究者开展社交媒体帖文的认知分析研究，例如探究个体对网络帖文的感知、解读与回应方式。针对大语言模型（LLM）的认知分析，不仅需分析用户指标与二分类虚假信息标签，更致力于揭示塑造社交媒体行为的潜在推理模式、态度与偏见。该研究视角对于理解为何部分虚假信息叙事能够实现病毒式传播、信念如何演变，以及哪些因素会影响用户对网络内容的信任或质疑态度，均具有至关重要的价值。