@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://aclanthology.org/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.",
}
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%0 Conference Proceedings
%T Transformer-based classification of premise in tweets related to COVID-19
%A Porvatov, Vadim
%A Semenova, Natalia
%Y Gonzalez-Hernandez, Graciela
%Y Weissenbacher, Davy
%S Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task
%D 2022
%8 October
%I Association for Computational Linguistics
%C Gyeongju, Republic of Korea
%F porvatov-semenova-2022-transformer
%X 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.
%U https://aclanthology.org/2022.smm4h-1.30
%P 108-110
Markdown (Informal)
[Transformer-based classification of premise in tweets related to COVID-19](https://aclanthology.org/2022.smm4h-1.30) (Porvatov & Semenova, SMM4H 2022)
ACL