Dataset of Annotated X (Twitter) Misinformation Posts with Human and Large Language Model (LLM) Responses for Cognitive Analysis
Published: 7 May 2025| Version 2 | DOI: 10.17632/r9g4twf8mz.2
Contributors:
Dominika Wojtczak, Cheryl McQuire, Ryan McConville, Luisa Zuccolo, Claudia PeersmanDescription
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.
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Institutions
- University of Bristol
Categories
Social Media, Machine Learning, Behavioral Psychology, Cognitive Bias, Misinformation Effect, Large Language Model
Funders
- Engineering and Physical Sciences Research CouncilUnited KingdomGrant ID: This work was supported by the EPSRC funder grant number EP/S022465/1.