Sentiment Analysis on Covid-19 Vaccinations in Ireland using Support Vector Machine

Abstract

Monitoring and analyzing social data is currently a norm to gauge public sentiments for efficiently marketing prod-ucts and services. With the recent outbreak of the Coronavirus disease 2019 (Covid-19) and subsequent vaccination programs, it became essential to spread awareness and understand the public sentiments on Covid-19 vaccines. This paper describes the life-cycle of conducting a Sentiment Analysis (SA) on the Covid-19 vaccination program in Ireland. Global and Irish Tweets were collected via Twitter API from January 2020 to August 2021. A lexicon and rule-based VADER tool labelled the global dataset as negative, positive, and neutral. After that, Irish tweets were classified into different sentiments using Support Vector Machine (SVM). Results show positive sentiment toward vaccines at the beginning of the vaccination drive, however, this sentiment gradually changed to negative in early 2021.