A Large-Scale Analysis of Persian Tweets Regarding Covid-19 Vaccination

TL;DR

This paper provides a comprehensive analysis of Iranian public opinion on Covid-19 vaccines using Twitter data, revealing emotional and thematic insights into vaccination attitudes and concerns.

Contribution

It introduces a novel combination of search, topic modeling, transformer-based classification, and emotion analysis to study vaccine-related discourse on social media.

Findings

Vaccine discussions focus on safety, hesitancy, and side effects.

Public emotions are significantly affected by vaccination and infection rates.

Twitter reveals diverse opinions and emotional responses about Covid-19 vaccines.

Abstract

The Covid-19 pandemic had an enormous effect on our lives, especially on people's interactions. By introducing Covid-19 vaccines, both positive and negative opinions were raised over the subject of taking vaccines or not. In this paper, using data gathered from Twitter, including tweets and user profiles, we offer a comprehensive analysis of public opinion in Iran about the Coronavirus vaccines. For this purpose, we applied a search query technique combined with a topic modeling approach to extract vaccine-related tweets. We utilized transformer-based models to classify the content of the tweets and extract themes revolving around vaccination. We also conducted an emotion analysis to evaluate the public happiness and anger around this topic. Our results demonstrate that Covid-19 vaccination has attracted considerable attention from different angles, such as governmental issues, safety or hesitancy, and side effects. Moreover, Coronavirus-relevant phenomena like public vaccination and the rate of infection deeply impacted public emotional status and users' interactions.