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