In a new preprint, Sami Nenno together with Kamil Fuławka and Philipp Lorenz-Spreen from our team and Cornelius Puschmann from the University of Bremen use a new text-based method to detect misinformation on social media. The study analyzes more than half a million posts from all German members of parliament and their official party accounts across Facebook, X, Instagram, and TikTok. Using a novel text-matching approach, the researchers link posts to over 5,000 fact-checking articles and 1,500 community notes. Compared to other methods, they identify ten times as many posts that contain misinformation.
