A Holistic Framework for Analyzing the COVID-19 Vaccine Debate

TL;DR

This paper introduces a comprehensive framework for analyzing the COVID-19 vaccine debate by integrating stance, reasoning, and moral sentiment analysis to better understand misinformation and decision-making.

Contribution

It presents a novel holistic analysis framework that models dependencies between different analysis levels and incorporates human insights, improving predictions in low-supervision scenarios.

Findings

Framework provides reliable predictions with limited supervision

Integrates stance, reasoning, and moral sentiment analysis

Models dependencies between analysis levels

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.