BERT Model for Fake News Detection Based on Social Bot Activities in the COVID-19 Pandemic

In the global pandemic, social media platforms are the primary source of information exchange. Social bots are one of the main sources of misinformation in the COVID-19 pandemic but do social bots spread the fake and real news with the same ratio as human accounts on social media platforms? Can bot detection improve fake news detection on social media platforms? Who presents more fake news in the COVID-19 pandemic, Human or social bots? This work provides preliminary research results based on limited data to answer these questions, but it opens a new perspective on fake news detection and bot detection on online platforms. We use Bidirectional Encoder Representations from Transformers(BERT) to create a new model for fake news detection. We use the transfer learning model to detect bot accounts in the COVID-19 data set. Then apply new features to improve the new fake news detection model in the COVID-19 data set.