Sentiment analysis and topic modeling for COVID-19 vaccine discussions

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.

[Retracted] Public View of Public Health Emergencies Based on Artificial Intelligence Data

“…Yanran Internet has become a “mirror” of real society. In the era of deep integration of the Internet and the real society, the trend of evolution, the influencing factors, and propagation paths of cyber views on public outbreaks are more difficult to approach than ever before [ 24 ]. Under this circumstance, it is very important to conduct uninterrupted investigations on the public views of network emergencies and restore the whole process of the development of network emergencies and public views [ 25 ].…”

Analyzing the public sentiment on COVID-19 vaccination in social media: Bangladesh context

“…Yin et al [ 22 ] conducted a study to analyze the public attitudes toward the Covid-19 vaccine. In addition, they identified the most common and discussed vaccine-related topics.…”

COVID-19 vaccine sensing: Sentiment analysis and subject distillation from twitter data

“…Yin et al . [32] used natural language processing to analyze popular topics and the emotional polarity of netizens in different countries towards different vaccine brands. It can be seen that the combination of sentiment analysis and topic clustering is widely used for analysing COVID-19 related texts in social media.…”