A Holistic Framework for Analyzing the COVID-19 Vaccine Debate

Maria Leonor Pacheco, Tunazzina Islam, Monal Mahajan, Andrey Shor, Ming Yin, Lyle Ungar, Dan Goldwasser


Abstract
The Covid-19 pandemic has led to infodemic of low quality information leading to poor health decisions. Combating the outcomes of this infodemic is not only a question of identifying false claims, but also reasoning about the decisions individuals make.In this work we propose a holistic analysis framework connecting stance and reason analysis, and fine-grained entity level moral sentiment analysis. We study how to model the dependencies between the different level of analysis and incorporate human insights into the learning process. Experiments show that our framework provides reliable predictions even in the low-supervision settings.
Anthology ID:
2022.naacl-main.427
Volume:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
July
Year:
2022
Address:
Seattle, United States
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5821–5839
Language:
URL:
https://aclanthology.org/2022.naacl-main.427
DOI:
10.18653/v1/2022.naacl-main.427
Bibkey:
Cite (ACL):
Maria Leonor Pacheco, Tunazzina Islam, Monal Mahajan, Andrey Shor, Ming Yin, Lyle Ungar, and Dan Goldwasser. 2022. A Holistic Framework for Analyzing the COVID-19 Vaccine Debate. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 5821–5839, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
A Holistic Framework for Analyzing the COVID-19 Vaccine Debate (Pacheco et al., NAACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.naacl-main.427.pdf
Code
 mlpacheco/covid-moral-foundations