<p>Fake news poses significant societal risks by spreading rapidly on social media. While existing research predominantly examines its propagation patterns and psychological drivers, the neural underpinnings remain insufficiently understood. Moreover, current studies often focus on Western political contexts, overlooking cultural variations where social-lifestyle fake news may be more prevalent, such as in China. In this paper, we introduce a multimodal dataset that combines neuroimaging, behavioral data, and standardized Chinese social-lifestyle fake and true news materials. The dataset includes T1 structural, resting-state, and task-based fMRI data from 43 college students, capturing brain activity during tasks involving sharing news and assessing its accuracy. Additionally, participants’ trait and rating data were collected to explore individual differences in brain structure, intrinsic functional states, and responses to fake and true news. This dataset could inform future studies on misinformation, offering deeper insights into the neural and psychological aspects of fake news. An overview of the data acquisition, cleaning, and sharing procedures is presented.</p>

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China’s social fake news database release with brain structural, functional, and behavioural measures

  • Wanting Chen,
  • Jia Shi,
  • Qinghua He

摘要

Fake news poses significant societal risks by spreading rapidly on social media. While existing research predominantly examines its propagation patterns and psychological drivers, the neural underpinnings remain insufficiently understood. Moreover, current studies often focus on Western political contexts, overlooking cultural variations where social-lifestyle fake news may be more prevalent, such as in China. In this paper, we introduce a multimodal dataset that combines neuroimaging, behavioral data, and standardized Chinese social-lifestyle fake and true news materials. The dataset includes T1 structural, resting-state, and task-based fMRI data from 43 college students, capturing brain activity during tasks involving sharing news and assessing its accuracy. Additionally, participants’ trait and rating data were collected to explore individual differences in brain structure, intrinsic functional states, and responses to fake and true news. This dataset could inform future studies on misinformation, offering deeper insights into the neural and psychological aspects of fake news. An overview of the data acquisition, cleaning, and sharing procedures is presented.