Detecting Conspiracy Theory Against COVID-19 Vaccines

TL;DR

This paper analyzes social media comments related to COVID-19 vaccines to identify conspiracy theories and assess sentiment and toxicity using BERT and Perspective API models.

Contribution

It introduces a method for detecting conspiracy theories against COVID-19 vaccines by applying sentiment and toxicity analysis on social media comments.

Findings

Identified prevalent conspiracy theories like 5G and bioweapons.

Demonstrated the effectiveness of BERT and Perspective API in sentiment analysis.

Highlighted the toxicity levels of conspiracy-related comments.

Abstract

Since the beginning of the vaccination trial, social media has been flooded with anti-vaccination comments and conspiracy beliefs. As the day passes, the number of COVID- 19 cases increases, and online platforms and a few news portals entertain sharing different conspiracy theories. The most popular conspiracy belief was the link between the 5G network spreading COVID-19 and the Chinese government spreading the virus as a bioweapon, which initially created racial hatred. Although some disbelief has less impact on society, others create massive destruction. For example, the 5G conspiracy led to the burn of the 5G Tower, and belief in the Chinese bioweapon story promoted an attack on the Asian-Americans. Another popular conspiracy belief was that Bill Gates spread this Coronavirus disease (COVID-19) by launching a mass vaccination program to track everyone. This Conspiracy belief creates distrust issues among laypeople and creates vaccine hesitancy. This study aims to discover the conspiracy theory against the vaccine on social platforms. We performed a sentiment analysis on the 598 unique sample comments related to COVID-19 vaccines. We used two different models, BERT and Perspective API, to find out the sentiment and toxicity of the sentence toward the COVID-19 vaccine.