APS
2022 APS Annual Convention · 2022
Qualitative and Quantitative Assessments of Topic Gists Extracted Using Machine Learning from Social Media Messages about COVID-19
- Megan Birmingham
Cornell University - Valerie Reyna
Cornell University - David Broniatowski
George Washington University - Demetrius Bryson
Cornell University - Sarah Edelson
Cornell University
Abstract
Machine-learning models were used to extract the gist of topics on social media during the COVID-19 pandemic, using fuzzy-trace theory as a framework. Extracted topics were rated as highly coherent by students and Mturkers. Social media topics about lockdowns and comparisons to flu have important implications for public health.
Risk
