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Fake news on social media has become a hot topic of research as it negativelyimpacts the discourse of real news in the public. Specifically, the ongoingCOVID-19 pandemic has seen a rise of inaccurate and misleading information dueto the surrounding controversies and unknown details at the beginning of thepandemic. The FakeNews task at MediaEval 2020 tackles this problem by creatinga challenge to automatically detect tweets containing misinformation based ontext and structure from Twitter follower network. In this paper, we present asimple approach that uses BERT embeddings and a shallow neural network forclassifying tweets using only text, and discuss our findings and limitations ofthe approach in text-based misinformation detection.

TIB's Visual Analytics Group at MediaEval '20: Detecting Fake News on Corona Virus and 5G Conspiracy