Chen Wanting, Shi Jia, He Qinghua
Department of Psychology, Zhejiang Sci-Tech University, Hangzhou, China.
Faculty of Psychology, Southwest University, Chongqing, China.
Sci Data. 2025 Mar 31;12(1):538. doi: 10.1038/s41597-025-04901-4.
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.
虚假新闻通过在社交媒体上迅速传播带来了重大的社会风险。虽然现有研究主要考察其传播模式和心理驱动因素，但对其神经基础的了解仍不充分。此外，当前研究往往聚焦于西方政治背景，忽视了社会生活类虚假新闻可能更为普遍的文化差异，比如在中国。在本文中，我们引入了一个多模态数据集，该数据集结合了神经成像、行为数据以及标准化的中文社会生活类真假新闻材料。该数据集包括来自43名大学生的T1结构像、静息态和基于任务的功能磁共振成像数据，记录了在涉及分享新闻和评估其准确性的任务过程中的大脑活动。此外，还收集了参与者的特质和评分数据，以探究大脑结构、内在功能状态以及对真假新闻反应方面的个体差异。这个数据集可以为未来关于错误信息的研究提供参考，更深入地洞察虚假新闻的神经和心理层面。本文还介绍了数据采集、清理和共享程序的概述。
