Global Reactions to COVID-19 Vaccine Brands on Twitter: Sentiments and Emotions Analysis

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Date
2021-12
Authors
Ye, Yu
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Townsend, Anthony
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NA, NA
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Abstract
Background: COVID-19 has had a significant impact on human beings in the areas of human care, job market, economy, and society in recent history. To prevent this infectious disease, vaccination is a cornerstone as a preventive measure. As a result, public bias, opinion, fear, and hesitancy may significantly impact the progression toward the herding community. Objective: This study aims to provide visibility of the public’s opinion and discussion topics of COVID-19 vaccine-related discussions on Twitter. Also, another goal is to discern the changes in topics and sentiments over time and events to better understand people’s perceptions, concerns, and emotions. Methods: Data were downloaded from Kaggle. The uploader scrapped the dataset using Tweepy from Twitter from September 30th, 2021. I used Python to clean the tweets (tokenization, stop words, lemmatization) and perform sentiment analysis, emotional analysis, and time series analysis. We retrieved publicly available tweets posted within the timeline of January 2020 to September 2021. Result: The natural sentiment is the dominant sentiment on Twitter, which accounts for 51%. Fear and surprises are the major emotions. The fluctuations of sentiments and emotions towards the Covid-19 pandemic and vaccine brands are highly associated with the Covid-19 related events.
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2021