Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

3-2022

Abstract

The COVID-19 pandemic has caused large scale health, economic, and social crisis. Scientists throughout the globe have been working on producing effective vaccines to combat this pandemic. COVID-19 vaccine release started in 2020, and low take-up rates among the public have been observed initially. There has been a soar in social media data on vaccines. This paper presents a comprehensive analysis of COVID-19 vaccine-related tweets. Sentiments shared by people through tweets and common topics have been extracted using classification and sentiment analysis. Our results showed a higher negative sentiment when the pandemic was declared, and it gradually changed to positive with the COVID-19 vaccine development/rollout. Tweet sentiment analysis offers health departments around the globe a quick sense of public sentiment towards the vaccine. Dominant topics or areas of concern have been identified using topic modelling that might need to be addressed.

Keywords

Vaccine sentiment analytics, COVID-19 vaccine, Text mining

Discipline

Categorical Data Analysis | Software Engineering

Research Areas

Data Science and Engineering

Publication

Proceedings of the IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC 2022) : Las Vegas, USA, January 26-29

First Page

467

Last Page

474

ISBN

9781665483049

Identifier

10.1109/CCWC54503.2022.9720793

Publisher

IEEE

City or Country

Las Vegas, USA

Comments

PDF provided by faculty.

Additional URL

https://doi.org/10.1109/CCWC54503.2022.9720793

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