FineFake: A Fine-grained Multi-domain Fake News Detection Dataset

FineFake is a dataset specifically designed for fine-grained multi-domain fake news detection, jointly created by Beihang University and Beijing University of Posts and Telecommunications.The dataset has a total of 16,909 data samples, covering 6 semantic topics and 8 different platforms.Each news sample contains multiple forms of content, including text, images, and potential social context information, and is semi-manually verified to verify common knowledge.

Different from the traditional true or false binary label,The annotations of the FineFake dataset provide a more fine-grained classification, which helps to reveal the strategies behind fake news more accurately. FineFake aims to solve the domain adaptability problem in fake news detection by providing data across topics and platforms to encourage researchers to develop detection models that can accurately identify and adapt to different news domains.