  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.
