Can Pharmacovigilance Be Performed on Social Media? Mining Adverse Vaccine Reactions From Twitter

Pharmacovigilance performed from social media data is an active research field that contributes to the automatic detection of adverse drug reactions (ADRs) of medications and vaccines. Natural language processing techniques combined with machine learning models are used to perform the challenging task of analyzing heterogeneous short text content. This study explores the application of state-of-the-art transfer learning approaches for classifying Spanish tweets to identify mentions of ADRs as a result of COVID-19 vaccination. We created a corpus of 1332 tweets about COVID-19 post-vaccination adverse reactions and employed language models for text classification. Preliminary results suggest that these models achieve superior performances in terms of F1 score compared to traditional machine learning models.