Twitters’ Concerns and Opinions About the COVID-19 Booster Shots: Infoveillance Study

Abstract Objective: This study aimed to categorize and analyze the public response toward third/booster shots of COVID-19 on Twitter. Methods: We downloaded the COVID-19 vaccine booster shots related Tweets using the Twitter API. The collected Tweets were pre-processed to prepare them for analysis by (1) removing non-English language tweets, retweets, emojis, emoticons, non-printable characters, the punctuation marks, and the prepositions, (2) anonymizing the identity of the users, and (3) normalizing various forms of the same words. We used the state-of-the-art BertTopic modeling library to identify the most popular topics. Results: Of 165,048 Tweets collected, 36,908 Tweets were analyzed in this study. From these tweets, we identified 9 topics, which were about Biden administration, Pfizer & BioNTech, Moderna, Johnson & Johnson, eligibility for booster shots, side effects, Donald Trump, variants of the Novel Coronavirus, and conspiracy theory & propaganda. The mean of sentiment was positive in all topics. The lowest and highest mean of sentiments were for the Donald Trump topic (0.0097) and the Johnson & Johnson topic (0.1294), respectively. Conclusions: The topics identified in this study not only accurately reflect the contemporary COVID-19 discussion, but also the high degree of politicization in the USA. While the latter might be a result of our rejection of non-English tweets, it is reassuring to see our fully automated, unsupervised pipeline reliably extract such global features in the data at scale. We, therefore, believe that the methodology presented in this study is mature and useful for other infoveillance studies on a wide variety of topics.