JMIR Publications

ABSTRACT

Background:

Though vaccination is a cornerstone for the prevention of communicable infectious diseases, vaccination has traditionally faced public fears, hesitancy. COVID-19 vaccines are no exception. Social media use plays a role in low acceptance of vaccines.

Objective:

This study will identify the topics and sentiments in the public COVID-19 vaccine-related discussion on social media and discern the salient changes in topics and sentiments over time in order to better understand the public perceptions, concerns, and emotions that may influence the achievement of herd immunity goals.

Methods:

Tweets were downloaded from a large-scale COVID-19 Twitter chatter data set from March 11, 2020, when the World Health Organization declared COVID-19 a pandemic, to January 31, 2020. We used R (The R Foundation) to clean the tweets and retain tweets that contained the following keywords: “vaccination", "vaccinations", "vaccine", "vaccines", "immunization", "vaccinate", and "vaccinated”. The final data set included in the analysis consisted of 1,499,421 unique tweets from 583,499 different users. We used R to perform the latent Dirichlet allocation algorithm for topic modeling as well as the sentiment and emotion analysis using the NRC (National Research Council in Canada) Emotion Lexicon.

Results:

Topic modeling COVID-19 vaccine tweets yielded 16 topics, which were grouped into 5 overarching themes. Opinions about vaccination (227,840 tweets, 15.2%) was the most tweeted topic and remained the hottest topic in majority of the time of our examination. Vaccine progress around the world once became the hottest topic around August 11, 2020 when Russia approved the world's first COVID vaccine. With the advancement of vaccine administration, the topic of instruction on getting vaccines gradually became more salient and leapt to the hottest topic after the first week of January, 2021. Weekly mean sentiment scores showed that despite fluctuations, in general, the sentiment was increasingly positive. Emotion analysis further showed that trust was the most predominant emotion, followed by anticipation, fear, and sadness etc. Trust reached its peak on November 19, 2020 when Pfizer announced that its vaccine is 90% effective.

Conclusions:

Public COVID-19 vaccine-related discussion on Twitter was largely driven by major events about COVID-19 vaccines and mirrored the hot news in mainstream media. Discussion also demonstrated a global perspective. The increasingly positive sentiment around COVID-19 vaccines and the dominant emotion of trust shown in the social media discussion may imply a higher COVID-19 vaccine acceptance compared with previous vaccines. Clinical Trial: N/P