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Public sentiment toward the COVID-19 vaccine as expressed on social media can interfere with communication by public health agencies on the importance of getting vaccinated. We investigated Twitter data to understand differences in sentiment, moral values, and language use between political ideologies on the COVID-19 vaccine. We estimated political ideology, conducted a sentiment analysis, and guided by the tenets of moral foundations theory (MFT), we analyzed 262,267 English language tweets from the United States containing COVID-19 vaccine-related keywords between May 2020 and October 2021. We applied the Moral Foundations Dictionary and used topic modeling and Word2Vec to understand moral values and the context of words central to the discussion of the vaccine debate. A quadratic trend showed that extreme ideologies of both Liberals and Conservatives expressed a higher negative sentiment than Moderates, with Conservatives expressing more negative sentiment than Liberals. Compared to Conservative tweets, we found the expression of Liberal tweets to be rooted in a wider set of moral values, associated with moral foundations of care (getting the vaccine for protection), fairness (having access to the vaccine), liberty (related to the vaccine mandate), and authority (trusting the vaccine mandate imposed by the government). Conservative tweets were found to be associated with harm (around safety of the vaccine) and oppression (around the government mandate). Furthermore, political ideology was associated with the expression of different meanings for the same words, e.g. “science” and “death.” Our results inform public health outreach communication strategies to best tailor vaccine information to different groups.
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Wording Matters: the Effect of Linguistic Characteristics and Political Ideology on Resharing of COVID-19 Vaccine Tweets
Social media platforms are frequently used to share information and opinions around vaccinations. The more often a message is reshared, the wider the reach of the message and potential influence it may have on shaping people’s opinions to get vaccinated or not. We used a negative binomial regression to investigate whether a message’s linguistic characteristics (degree of concreteness, emotional arousal, and sentiment) and user characteristics (political ideology and number of followers) may influence users’ decisions to reshare tweets related to the COVID-19 vaccine. We analyzed US English-language tweets related to the COVID-19 vaccine between May 2020 and October 2021 (N = 236,054). Tweets with positive and high-arousal words were more often retweeted than negative, low-arousal tweets. Tweets with abstract words were more often retweeted than tweets with concrete words. In addition, while Liberal users were more likely to have tweets with a positive sentiment reshared, Conservative users were more likely to have tweets with a negative sentiment reshared. Our results can inform public health messaging on how to best phrase vaccine information to impact engagement and information resharing, and potentially persuade a wider set of people to get vaccinated.
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- Award ID(s):
- 2107150
- PAR ID:
- 10542640
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- ACM Transactions on Computer-Human Interaction
- ISSN:
- 1073-0516
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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The COVID-19 pandemic has been sweeping across the United States of America since early 2020. The whole world was waiting for vaccination to end this pandemic. Since the approval of the first vaccine by the U.S. CDC on 9 November 2020, nearly 67.5% of the US population have been fully vaccinated by 10 July 2022. While quite successful in controlling the spreading of COVID-19, there were voices against vaccines. Therefore, this research utilizes geo-tweets and Bayesian-based method to investigate public opinions towards vaccines based on (1) the spatiotemporal changes in public engagement and public sentiment; (2) how the public engagement and sentiment react to different vaccine-related topics; (3) how various races behave differently. We connected the phenomenon observed to real-time and historical events. We found that in general the public is positive towards COVID-19 vaccines. Public sentiment positivity went up as more people were vaccinated. Public sentiment on specific topics varied in different periods. African Americans’ sentiment toward vaccines was relatively lower than other races.more » « less
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Background As a number of vaccines for COVID-19 are given emergency use authorization by local health agencies and are being administered in multiple countries, it is crucial to gain public trust in these vaccines to ensure herd immunity through vaccination. One way to gauge public sentiment regarding vaccines for the goal of increasing vaccination rates is by analyzing social media such as Twitter. Objective The goal of this research was to understand public sentiment toward COVID-19 vaccines by analyzing discussions about the vaccines on social media for a period of 60 days when the vaccines were started in the United States. Using the combination of topic detection and sentiment analysis, we identified different types of concerns regarding vaccines that were expressed by different groups of the public on social media. Methods To better understand public sentiment, we collected tweets for exactly 60 days starting from December 16, 2020 that contained hashtags or keywords related to COVID-19 vaccines. We detected and analyzed different topics of discussion of these tweets as well as their emotional content. Vaccine topics were identified by nonnegative matrix factorization, and emotional content was identified using the Valence Aware Dictionary and sEntiment Reasoner sentiment analysis library as well as by using sentence bidirectional encoder representations from transformer embeddings and comparing the embedding to different emotions using cosine similarity. Results After removing all duplicates and retweets, 7,948,886 tweets were collected during the 60-day time period. Topic modeling resulted in 50 topics; of those, we selected 12 topics with the highest volume of tweets for analysis. Administration and access to vaccines were some of the major concerns of the public. Additionally, we classified the tweets in each topic into 1 of the 5 emotions and found fear to be the leading emotion in the tweets, followed by joy. Conclusions This research focused not only on negative emotions that may have led to vaccine hesitancy but also on positive emotions toward the vaccine. By identifying both positive and negative emotions, we were able to identify the public's response to the vaccines overall and to news events related to the vaccines. These results are useful for developing plans for disseminating authoritative health information and for better communication to build understanding and trust.more » « less
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Wardman, Jamie (Ed.)Currently, one of the most pressing public health challenges is encouraging people to get vaccinated against COVID-19. Due to limited supplies, some people have had to wait for the COVID-19 vaccine. Consumer research has suggested that people who are overlooked in initial distribution of desired goods may no longer be interested. Here, we therefore examined people’s preferences for proposed vaccine allocation strategies, as well as their anticipated responses to being overlooked. After health-care workers, most participants preferred prioritizing vaccines for high-risk individuals living in group-settings (49%) or with families (29%). We also found evidence of reluctance if passed over. After random assignment to vaccine allocation strategies that would initially overlook them, 37% of participants indicated that they would refuse the vaccine. The refusal rate rose to 42% when the vaccine allocation strategy prioritized people in areas with more COVID-19 – policies that were implemented in many areas. Even among participants who did not self-identify as vaccine hesitant, 22% said they would not want the vaccine in that case. Logistic regressions confirmed that vaccine refusal would be largest if vaccine allocation strategies targeted people who live in areas with more COVID-19 infections. In sum, once people are overlooked by vaccine allocation, they may no longer want to get vaccinated, even if they were not originally vaccine hesitant. Vaccine allocation strategies that prioritize high-infection areas and high-risk individuals in group-settings may enhance these concerns.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3637876
