Abstract

The outbreak of the novel coronavirus disease (COVID-19) has been ongoing for almost two years and has had an unprecedented impact on the daily lives of people around the world. More recently, the emergence of the Delta variant of COVID-19 has once again put the world at risk. Fortunately, many countries and companies have developed vaccines for the coronavirus. As of 23 August 2021, more than 20 vaccines have been approved by the World Health Organization (WHO), bringing light to people besieged by the pandemic. The global rollout of the COVID-19 vaccine has sparked much discussion on social media platforms, such as the effectiveness and safety of the vaccine. However, there has not been much systematic analysis of public opinion on the COVID-19 vaccine. In this study, we conduct an in-depth analysis of the discussions related to the COVID-19 vaccine on Twitter. We analyze the hot topics discussed by people and the corresponding emotional polarity from the perspective of countries and vaccine brands. The results show that most people trust the effectiveness of vaccines and are willing to get vaccinated. In contrast, negative tweets tended to be associated with news reports of post-vaccination deaths, vaccine shortages, and post-injection side effects. Overall, this study uses popular Natural Language Processing (NLP) technologies to mine people’s opinions on the COVID-19 vaccine on social media and objectively analyze and visualize them. Our findings can improve the readability of the confusing information on social media platforms and provide effective data support for the government and policy makers.

Highlights

  • The outbreak of the novel coronavirus disease (COVID-19) has caused immeasurable losses to the world and affected the normal lives of billions of people around the world

  • This study conducted a comprehensive analysis of COVID-19 vaccine-related tweets collected from Twitter between December 12, 2020 and July 2, 2021

  • The sentiment analysis results showed that the overall sentiment polarity is positive, and the number of positive tweets is approximate twice as much as the number of negative tweets

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Summary

Introduction

The outbreak of the novel coronavirus disease (COVID-19) has caused immeasurable losses to the world and affected the normal lives of billions of people around the world. Many countries and regions have adopted a series of specific measures to help slow down the spread of COVID-19. Such as closing borders, reducing the activities in public places (e.g., restaurants, gyms, shopping centers), working/studying from home, restricting travel distance and maintaining good hygiene. The discussions of the COVID-19 vaccine on social media provide us with a source of data to find out people’s concerns about the vaccine. This paper examines the discussions about the COVID-19 vaccine on Twitter, extracts the topics and the sentiment polarity in the tweets. – To the best of our knowledge, this is the first analysis of the public discussions related to the COVID-19 vaccines on social media since the emergence of the COVID-19 Delta variant.

Related work
Sentiment analysis for COVID‐19 based on social media
Infodemic analysis for COVID‐19 based on social media
Analysis of COVID‐19 vaccine discussions on social media
Data preprocessing and statistics
Adopted methods for topic modeling and sentiment analysis
Measuring tweet sentiment
Topic modeling of tweets
Experimental results and analysis
Prevalent emotional words by vaccines
Sentiment analysis of tweets
Conclusion
Full Text
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