Exploration of COVID-19 Discourse on Twitter: American Politician Edition
Journal:
arXiv
Published Date:
May 8, 2025
Abstract
The advent of the COVID-19 pandemic has undoubtedly affected the political
scene worldwide and the introduction of new terminology and public opinions
regarding the virus has further polarized partisan stances. Using a collection
of tweets gathered from leading American political figures online (Republican
and Democratic), we explored the partisan differences in approach, response,
and attitude towards handling the international crisis. Implementation of the
bag-of-words, bigram, and TF-IDF models was used to identify and analyze
keywords, topics, and overall sentiments from each party. Results suggest that
Democrats are more concerned with the casualties of the pandemic, and give more
medical precautions and recommendations to the public whereas Republicans are
more invested in political responsibilities such as keeping the public updated
through media and carefully watching the progress of the virus. We propose a
systematic approach to predict and distinguish a tweet's political stance (left
or right leaning) based on its COVID-19 related terms using different
classification algorithms on different language models.
