Automatic detection of fake tweets about Covid-19 Vaccine in Portuguese

The Covid-19 pandemic induced an unprecedented wave of disinformation in social networks. This had dire consequences for society. The situation was particularly serious in Brazil due to official support for unproven treatments and denial of vaccine effectiveness. Political polarization helped to create an explosion of false tweets in Portuguese, which constitutes a threat to public health. An algorithm that could discriminate between true and false messages would be a very important tool to reduce or even stop the wave of disinformation. We developed BERTVacPort, an approach to automatically and reliably label tweets about vaccines in Portuguese as reliable or fake. The architecture relies upon a pre-trained Portuguese BERT-like transformer base Neural Network with two extra fully-connected layers. To train the implementation we collected almost 3 million tweets containing the word vacina, vaccine in Portuguese, over a 7 month period. We classified a fraction of the corpus (16,731 tweets) and used it to fine-tune the algorithm. The best results were achieved when retrained the last seven layers of the BERT-like network and the two additional layers. We obtained 74% f1-score and 74% accuracy. Considering the heterogeneity of the database and the ambiguity of many messages limited to 280 characters, the results are probably as good as possible and outperform a human reader.