#Detecting COVID-19 Health-Related Misinformation in Social Media
This repository describes the metods, problems, and dataset used for our project titled "detecting COVID-19 health-related misinformation in social media". This project proposal was first initiated during a competition (COVID-19 Transdisciplinary Team Grand Challenge 2020) arranged by UTSA graduate school and Office of the Vice President for Research, Economic Development, and Knowledge Enterprise. This trandisciplinary project proposal to tackle one of the COVID-19 related social issues has been awarded "1st place" during the challenge. Our project has leveraged research methods from Machine Learning, NLP, Social Psycohology fields to understand how health related misinformation is disseminating in social media such as Twitter, how we can identify them, methods to show the efficacy of detection mechanisms. We hope our project is a stepping stone to understand and limit the disruptions of public health at large during the COVID-19 pandemic.
We will keep updating the dataset, and other resources in this repository.
Update April 8, 2021: This work is submitted for publication at CySoc 2021 (International Workshop on Cyber Social Threats), which is under review at this moment.