Transformer-based classification of premise in tweets related to COVID-19

Vadim Porvatov, Natalia Semenova

Abstract: Automation of social network data assessment is one of the classic challenges of natural language processing. During the COVID-19 pandemic, mining people’s stances from their public messages become crucial regarding the understanding of attitude towards health orders. In this paper, authors propose the transformer-based predictive model allowing to effectively classify presence of stance and premise in the Twitter texts.