@inproceedings{porvatov-semenova-2022-transformer,
    title = "Transformer-based classification of premise in tweets related to {COVID}-19",
    author = "Porvatov, Vadim  and
      Semenova, Natalia",
    editor = "Gonzalez-Hernandez, Graciela  and
      Weissenbacher, Davy",
    booktitle = "Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop {\&} Shared Task",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2022.smm4h-1.30/",
    pages = "108--110",
    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."
}