Source
COLING SMM
DATE OF PUBLICATION
10/03/2022
Authors
Vadim Porvatov Natalia Semenova
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5q032e@SMM4H’22: Transformer-based classification of premise in tweets related to COVID-19

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.

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