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. 2021 Sep 15;39(39):5499-5505.
doi: 10.1016/j.vaccine.2021.08.058. Epub 2021 Aug 17.

Public attitudes toward COVID-19 vaccines on English-language Twitter: A sentiment analysis

Siru Liu  1 , Jialin Liu  2
Affiliations

Public attitudes toward COVID-19 vaccines on English-language Twitter: A sentiment analysis

Siru Liu et al. Vaccine. .

Abstract

Objective: To identify themes and temporal trends in the sentiment of COVID-19 vaccine-related tweets and to explore variations in sentiment at world national and United States state levels.

Methods: We collected English-language tweets related to COVID-19 vaccines posted between November 1, 2020, and January 31, 2021. We applied the Valence Aware Dictionary and sEntiment Reasoner tool to calculate the compound score to determine whether the sentiment mentioned in each tweet was positive (compound ≥ 0.05), neutral (-0.05 < compound < 0.05), or negative (compound ≤ -0.05). We applied the latent Dirichlet allocation analysis to extract main topics for tweets with positive and negative sentiment. Then we performed a temporal analysis to identify time trends and a geographic analysis to explore sentiment differences in tweets posted in different locations.

Results: Out of a total of 2,678,372 COVID-19 vaccine-related tweets, tweets with positive, neutral, and negative sentiments were 42.8%, 26.9%, and 30.3%, respectively. We identified five themes for positive sentiment tweets (trial results, administration, life, information, and efficacy) and five themes for negative sentiment tweets (trial results, conspiracy, trust, effectiveness, and administration). On November 9, 2020, the sentiment score increased significantly (score = 0.234, p = 0.001), then slowly decreased to a neutral sentiment in late December and was maintained until the end of January. At the country level, tweets posted in Brazil had the lowest sentiment score of -0.002, while tweets posted in the United Arab Emirates had the highest sentiment score of 0.162. The overall average sentiment score for the United States was 0.089, with Washington, DC having the highest sentiment score of 0.144 and Wyoming having the lowest sentiment score of 0.036.

Conclusions: Public sentiment on COVID-19 vaccines varied significantly over time and geography. Sentiment analysis can provide timely insights into public sentiment toward the COVID-19 vaccine and guide public health policymakers in designing locally tailored vaccine education programs.

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Conflict of interest statement

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Distribution of daily average sentiment score (yellow dots). The solid line is the 14-day moving average of sentiment scores. The diamond markers in red are change points. The green line indicates the date of the first effective vaccine announcement (November 9, 2020). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 2
Fig. 2
Distribution of tweets related to COVID-19 across sentiment types.
Fig. 3
Fig. 3
Heat map of the average sentiment score by country. The countries with<1000 tweets in English were shown in grey.
Fig. 4
Fig. 4
Average sentiment score and its error bar in each state in the United States.
Fig. 5
Fig. 5
Heat map of the state's average sentiment score in the United States in each month. (a. November 2020; b. December 2020; c. January 2021).
See this image and copyright information in PMC

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