Abstract

This paper focuses on examining and outlining how machines can be trained to recognize trends associated with human perceptions as it relates to the COVID-19 vaccination. Social media especially the Twitter platform has proven to be a viable source for identifying actionable data from people of diverse backgrounds in near real time. These data provide researchers the options of carrying out timeseries analysis, hot-spot analysis, situational awareness, and attitudes towards a particular trend etc. Our concern therefore, is to analyze people's perception towards vaccinations given public controversy in the United States and other countries. The methodology employed is the empirical study and model analysis.