Paper Link: https://openreview.net/forum?id=sSTn26Y2oc
Paper Type: Long paper (up to eight pages of content + unlimited references and appendices)
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.
Presentation Mode: This paper will be presented in person in Seattle
Copyright Consent Signature (type Name Or NA If Not Transferrable): Maria Leonor Pacheco
Copyright Consent Name And Address: Department of Computer Science, Purdue University. 305 N University St, West Lafayette, IN 47907