Verifee Dataset

Verifee数据集是由查尔斯大学社会科学学院和伦敦大学学院的研究人员共同创建，包含超过10,000篇来自近60个捷克在线新闻源的独特新闻文章。该数据集通过详细的信任度评估方法，将文章分为四个信任度类别，从完全可信到操纵性文章。数据集创建过程中，研究团队采用了多学科方法，邀请了来自社会科学、媒体科学和计算机科学的研究人员参与。该数据集旨在通过提供高质量的信任度评估数据，帮助开发和测试用于识别虚假新闻和提高媒体素养的AI工具。

The Verifee Dataset was co-created by researchers from the Faculty of Social Sciences of Charles University and University College London. It contains over 10,000 unique news articles sourced from nearly 60 Czech online news outlets. Using a rigorous trustworthiness evaluation methodology, the articles are classified into four trustworthiness categories, ranging from fully credible pieces to manipulative news articles. During the dataset's development process, the research team adopted a multidisciplinary approach, inviting researchers from social sciences, media science, and computer science to participate. This dataset aims to provide high-quality trustworthiness assessment data to aid the development and testing of AI tools for identifying fake news and enhancing media literacy.