Abstract
The understanding of the public response to COVID-19 vaccines is the key success factor to control the COVID-19 pandemic. To understand the public response, there is a need to explore public opinion. Traditional surveys are expensive and time-consuming, address limited health topics, and obtain small-scale data. Twitter can provide a great opportunity to understand public opinion regarding COVID-19 vaccines. The current study proposes an approach using computational and human coding methods to collect and analyze a large number of tweets to provide a wider perspective on the COVID-19 vaccine. This study identifies the sentiment of tweets using a machine learning rule-based approach, discovers major topics, explores temporal trend and compares topics of negative and non-negative tweets using statistical tests, and discloses top topics of tweets having negative and non-negative sentiment. Our findings show that the negative sentiment regarding the COVID-19 vaccine had a decreasing trend between November 2020 and February 2021. We found Twitter users have discussed a wide range of topics from vaccination sites to the 2020 U.S. election between November 2020 and February 2021. The findings show that there was a significant difference between tweets having negative and non-negative sentiment regarding the weight of most topics. Our results also indicate that the negative and non-negative tweets had different topic priorities and focuses. This research illustrates that Twitter data can be used to explore public opinion regarding the COVID-19 vaccine.
Highlights
Since 2020, some studies have utilized Twitter data to understand different issues related to the COVID-19 vaccine, such as exploring public opinion regarding vaccine hesitancy [33,34], vaccination in November 2020 [35], sentiment analysis of tweets posted between 1 March and 22 November 2020 [36], manual coding and content analysis of tweets posted between 1 and 22 November 2020 [37], misinformation [38,39], Spanish pro-vaccine campaign on Twitter between 14 and 28 December 2020 [40], anti-vaccination tweets posted between 1 January and 23 August, 2020 [41], and race-related discussions [42]
This study addressed the following four research questions: (1) How did the sentiment of tweets related to the COVID-19 vaccine change between November 2020 and February
2021?, (2) What are the main topics in tweets related to the COVID-19 vaccine?, (3) Is there a significant difference between topics in negative and non-negative tweets?, and (4) What are the top topics in negative and non-negative tweets? We found that the negative and non-negative sentiment of tweets containing terms related to the COVID-19 vaccine had decreasing and increasing trends, respectively
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. A large number of studies have utilized Twitter data to understand public discussions around the COVID-19 pandemic. Since 2020, some studies have utilized Twitter data to understand different issues related to the COVID-19 vaccine, such as exploring public opinion regarding vaccine hesitancy [33,34], vaccination in November 2020 [35], sentiment analysis of tweets posted between 1 March and 22 November 2020 [36], manual coding and content analysis of tweets posted between 1 and 22 November 2020 [37], misinformation [38,39], Spanish pro-vaccine campaign on Twitter between 14 and 28 December 2020 [40], anti-vaccination tweets posted between 1 January and 23 August, 2020 [41], and race-related discussions [42]. We identify top topics of negative and non-negative tweets
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