Understanding People's Perceptions Toward COVID-19 Vaccination Using Twitter Data

Twitter is a powerful social media platform where users can share public messages (tweets) about their personal experiences, including their health-related issues. It is important to have this candid, unfiltered feedback in healthcare and public health communication spaces, where patients may not be comfortable divulging personal information to healthcare teams, and randomly selected patients may not wish to participate in surveys about their experience. In this study, we propose to use the RoBERTa model, a transformer-based neural network, to perform sentiment analysis, and NRC Emotion Lexicon to perform emotion analysis, on COVID-19 related tweets to identify patient challenges and needs in healthcare systems. We will also apply a systems management approach to classify challenges in current healthcare systems in developed countries. Our study aims to demonstrate the effectiveness of RoBERTa for Natural Language Processing (NLP) in public health communications analysis.