Twitter Sentiment Analysis of Covid Vacciness
Wenbo Zhu Tiechuan Hu
In this paper, we look at a database of tweets sorted by various keywords
that could indicate the users sentiment towards covid vaccines. With social
media becoming such a prevalent source of opinion, sorting and ranking tweets
that hold important information such as opinions on covid vaccines is of utmost
importance. Two different ranking scales were used, and ranking a tweet in this
way could represent the difference between an opinion being lost and an opinion
being featured on the site, which affects the decisions and behavior of people,
and why researchers were interested in it. Using natural language processing
techniques, our aim is to determine and categorize opinions about covid
vaccines with the highest accuracy possible.