COVID-19 Vaccine Discourse on Twitter: A Content Analysis of Persuasion Techniques, Sentiment and Mis/Disinformation

Misinformation and COVID-19 vaccine uptake hesitancy among frontline workers in Tanzania: Do demographic variables matter?

Although COVID-19 vaccination has been widely considered as an important remedy to confront COVID-19, people remain hesitant to take it. The objective of this study was to assess the moderation effects of demographic characteristics on the relationship between forms of misinformation and COVID-19 vaccine uptake hesitancy among frontline workers in Dar es Salaam and Dodoma, Tanzania. Using a sample of 200 respondents, it assessed the differences in ratings on misinformation regarding COVID-19 vaccine based on respondents' demographics. The study used a Five-point Likert scale questionnaire distributed through snowball sampling to frontline workers from Dar es Salaam and Dodoma regions. Data was analyzed using binary logistic regression. It was found that the forms of misinformation revealed were manipulated imposters, satire, fabricated contents and false contents with their connection, which they influenced COVID-19 hesitancy significantly. With exception of age, that significantly moderated hesitancy, this study uncovers that, sex and education level moderated insignificantly in predicting those who are misinformed; misinformed individuals are not any less educated or not based on one's sex, different than individuals who are informed. The study informs policy makers on devising appropriate strategies to promote COVID-19 vaccination uptake among the different contextual demographic variables. Promotion of information, media and health literacy to the general public should be considered to deter spreading of vaccine-related misinformation.

COVID-19 Vaccine Boundary Work: The Case of Facebook Comments in Southeast Georgia

Although much research has considered the worldview of the vaccine hesitant, little attention has been given to the cultural conflict over what it means to be a person who takes vaccines. Through a qualitative content analysis of comments made on the Facebook pages of media outlets serving southeast Georgia, this analysis identifies both motives for rejecting the vaccine and outlines the symbolic boundaries that the vaccine hesitant have erected to distinguish themselves from vaccine advocates. The motives include perfunctory rejections, claims that the vaccine is ineffective, illegitimate, injurious in the short and long term, poisonous, infectious, particularly dangerous for children, and a component of conspiracy theories. These symbolic boundaries include distinguishing vaccine advocates from the vaccine hesitant by personal characteristics such as irrationality and authoritarianism. There are also social boundaries rooted in social locations - namely conservatives vs. liberals and non-elites vs. elites. This study also demonstrates how vaccine proponents engage with these symbolic boundaries. Vaccine proponents both contest and accept these boundaries. Likewise, pro-vaccine comments vary in terms of whether they stigmatize the boundary between vaccine user and non-user. This study adds to the literature on health communication and vaccines by confirming previous reports of the reasons for not taking the COVID-19 vaccine, indicating that public communication on vaccines is not regionally specific, and demonstrating the role that ostensible vaccine advocates might play in contributing to vaccine hesitancy.

Meaningful Media Experiences and Vaccination Message Communication: An Experimental Study with Vaccine-Hesitant Individuals

Guided by the eudaimonic media and the health persuasion literature, the current study explores how meaningful emotions elicited from entertainment media exposure decreases anti-vaccination attitudes among vaccine-hesitant individuals. Results of a between-subjects experiment (N = 409) showed that participants who viewed meaningful music videos (vs. neutral videos) and vaccination messages embedded in the user-generated comments reported more empathy, less reactance, and less anti-vaccination attitudes. Multigroup analysis revealed that this association was held for participants who were hesitant about whether they would get fully vaccinated, but not for participants who were determined to not get vaccinated. Theoretical and practical implications were discussed.

'Are you vaccinated? Yeah, I'm immunized': a risk orders theory analysis of celebrity COVID-19 misinformation

BACKGROUND

On 11 March 2020, COVID-19 was declared a global health pandemic by the World Health Organization (WHO). Vaccinating populations is paramount in changing the course of a pandemic. The rapid spread of (mis) and disinformation online from celebrities, politicians, and media influencers creates a corrosion of trust in public health interventions.

METHODS

Given the importance of the spread of information during a public health crisis, the current study uses risk orders theory with a constructivist grounded theory approach to analyze an episode of a popular podcast available on YouTube, titled, 'Aaron Rodgers Tells Pat McAfee His Side of Vaccine Situation.'

RESULTS

Findings illuminated three themes concerning COVID-19 medical interventions from celebrity discourse: (1) misinterpreting medical terminology; (2) conflating bodily autonomy and altruism; and (3) political ideology as an impetus for misinformation.

CONCLUSIONS

The discussion offers implications for healthcare practitioners in debunking mis- and disinformation. Foremost, lack of transparency concerning autonomy, liberty, freedom, and choice from public health experts who design messages during a public health crisis creates a space for non-medical influencers to promote pseudoscience, misinformation, and disinformation. This leads to public distrust of medical experts and confuses the public's understanding of best practices based upon standard of medical evidence and care.

"What Do I Say? How Do I Say it?" Twitter as a Knowledge Dissemination Tool for Mental Health Research

This study aims to generate evidence-based guidelines for researchers regarding how to effectively disseminate mental health research via Twitter. Three hundred mental health research Tweets posted from September 2018 to September 2019 were sampled from two large Australian organizations. Twenty-seven predictor variables were coded for each Tweet across five thematic categories: messaging; research area; mental health area; external networks; and media features. Regression analyses were conducted to determine associations with engagement outcomes of Favourites, Retweets, and Comments. Less than half (n = 10) of predictor variables passed validity tests. Notably, conclusions could not reliably be drawn on whether a Tweet featured evidence-based information. Tweets were significantly more likely to be Retweeted if they contained a hyperlink or multimedia. Tweets were significantly more likely to receive comments if they focused on a specific population group. These associations remain significant when controlling for organization. These findings indicate that researchers may be able to maximize engagement on Twitter by highlighting the population groups that the research applies to and enriching Tweets with multimedia content. In addition, care should be taken to ensure users can infer which messages are evidence-based. Guidelines and an accompanying resource are proposed.

'Vaccine as a cheat sheet': a metaphor gone awry on Facebook

COVID-19 vaccine-related conspiracy narratives skyrocketed in social media in the first year of the pandemic. Science communicators have tried to debunk false information as did Vlad Mixich, a Romanian public health expert, who tried to explain on Facebook why the vaccine cannot modify the human DNA. Drawing on the literature on metaphor as a discourse phenomenon, this paper uses a discourse-led approach to metaphor analysis to identify and analyze the metaphors used by Mixich to explain how vaccines work and the mRNA technology underlying the COVID-19 vaccine. A particular metaphor is then given special attention: 'vaccine as a cheat sheet'. The author of the Facebook post seems to use this metaphor deliberately both to clarify vaccine-related information and to mock people susceptible to false information about the vaccine. This paper shows that while the 'cheating' metaphor simplifies abstract knowledge and allows the audience to engage with a complex topic, it also has potential to amplify vaccine-related polarization.

Tracking the structure and sentiment of vaccination discussions on Mumsnet

Vaccination is one of the most impactful healthcare interventions in terms of lives saved at a given cost, leading the anti-vaccination movement to be identified as one of the top 10 threats to global health in 2019 by the World Health Organization. This issue increased in importance during the COVID-19 pandemic where, despite good overall adherence to vaccination, specific communities still showed high rates of refusal. Online social media has been identified as a breeding ground for anti-vaccination discussions. In this work, we study how vaccination discussions are conducted in the discussion forum of Mumsnet, a UK-based website aimed at parents. By representing vaccination discussions as networks of social interactions, we can apply techniques from network analysis to characterize these discussions, namely network comparison, a task aimed at quantifying similarities and differences between networks. Using network comparison based on graphlets-small connected network subgraphs-we show how the topological structure of vaccination discussions on Mumsnet differs over time, in particular before and after COVID-19. We also perform sentiment analysis on the content of the discussions and show how the sentiment toward vaccinations changes over time. Our results highlight an association between differences in network structure and changes to sentiment, demonstrating how network comparison can be used as a tool to guide and enhance the conclusions from sentiment analysis.

Addressing message fatigue for encouraging COVID-19 vaccination

During the prolonged COVID-19 pandemic, health communication researchers and practitioners should be aware of the unintended effects of message fatigue. Message fatigue is a motivational state caused by repeated and prolonged exposure to similar health-related messages that induces resistance to health behaviors. Messages encouraging COVID-19 vaccination tend to focus on scientific evidence and efficacy information. However, prolonged exposure to similarly framed repeated pro-COVID-19 vaccination messages may cause message fatigue, generate psychological reactance, and lead to ineffective persuasive outcomes. Scholars of message fatigue argue that health communication practitioners should select a less common frame to reduce fatigue responses and increase favorable attitudes toward message recommendations. Entering the second year since COVID-19 vaccination has begun, to reduce message fatigue, future pro-COVID-19 vaccination communication should increase the diversity of messages different than the frequently used types. This opinion piece proposes alternative dissemination of cognitive, affective, narrative, and non-narrative pro-COVID-19 vaccination messages.

Topics in Antivax and Provax Discourse: Yearlong Synoptic Study of COVID-19 Vaccine Tweets

BACKGROUND

Developing an understanding of the public discourse on COVID-19 vaccination on social media is important not only for addressing the ongoing COVID-19 pandemic but also for future pathogen outbreaks. There are various research efforts in this domain, although, a need still exists for a comprehensive topic-wise analysis of tweets in favor of and against COVID-19 vaccines.

OBJECTIVE

This study characterizes the discussion points in favor of and against COVID-19 vaccines posted on Twitter during the first year of the pandemic. The aim of this study was primarily to contrast the views expressed by both camps, their respective activity patterns, and their correlation with vaccine-related events. A further aim was to gauge the genuineness of the concerns expressed in antivax tweets.

METHODS

We examined a Twitter data set containing 75 million English tweets discussing the COVID-19 vaccination from March 2020 to March 2021. We trained a stance detection algorithm using natural language processing techniques to classify tweets as antivax or provax and examined the main topics of discourse using topic modeling techniques.

RESULTS

Provax tweets (37 million) far outnumbered antivax tweets (10 million) and focused mostly on vaccine development, whereas antivax tweets covered a wide range of topics, including opposition to vaccine mandate and concerns about safety. Although some antivax tweets included genuine concerns, there was a large amount of falsehood. Both stances discussed many of the same topics from opposite viewpoints. Memes and jokes were among the most retweeted messages. Most tweets from both stances (9,007,481/10,566,679, 85.24% antivax and 24,463,708/37,044,507, 66.03% provax tweets) came from dual-stance users who posted both provax and antivax tweets during the observation period.

CONCLUSIONS

This study is a comprehensive account of COVID-19 vaccine discourse in the English language on Twitter from March 2020 to March 2021. The broad range of discussion points covered almost the entire conversation, and their temporal dynamics revealed a significant correlation with COVID-19 vaccine-related events. We did not find any evidence of polarization and prevalence of antivax discourse over Twitter. However, targeted countering of falsehoods is important because only a small fraction of antivax discourse touched on a genuine issue. Future research should examine the role of memes and humor in driving web-based social media activity.

The doctor knows or the evidence shows: An online survey experiment testing the effects of source trust, pro-vaccine evidence, and dual-processing in expert messages recommending child COVID-19 vaccination to parents

Increasing child vaccination rates is a critical step toward mitigating the spread of COVID-19. Both distrust in expert sources and concern about the safety and efficacy of vaccines may contribute to parent vaccine hesitancy. The present study is the first to test the effectiveness of building trust and providing evidence supporting child COVID-19 vaccines in recommendation messages for parents. Based on dual-processing theories, emphasis on source trustworthiness and pro-vaccine evidence may each be particularly effective when the other is not present. It was hypothesized that these two approaches would have main and interaction effects on perceived message effectiveness and pro-vaccine beliefs. A between-subjects 2 (trust-building appeal vs. no trust-building appeal) X 2 (pro-vaccine evidence vs. no pro-vaccine evidence) online survey experiment was conducted in December 2021 and January 2022 with United States parents/guardians of children <18 years old (n = 401). As hypothesized, trust and pro-vaccine evidence each had significant simple main effects on both outcomes. Analysis of variance showed a significant negative interaction effect of trust and pro-vaccine evidence on perceived message effectiveness [F(3, 394) = 6.47; η2 = 0.02, p = 0.002; 95% CI (0.01, 0.11)], supporting the dual-processing hypothesis. The interaction effect on pro-vaccine beliefs was also negative but not significant [F(3, 394) = 2.69; η2 = 0.01; p = 0.102; 95% CI (0.00, 0.03)]. Either highlighting evidence supporting vaccines or building trust in expert sources can influence parent vaccine support. Messages which include strong evidence supporting recommended behaviors may influence recommendation acceptance even among those with lower trust in expert sources and establishing trust may reduce the need to describe available evidence.

A Comparative Case Study Analysis: Applying the HIPE Framework to Combat Harmful Health Information and Drive COVID-19 Vaccine Adoption in Underserved Communities

This descriptive, observational paper utilizes the comparative case study approach to analyze the application of the HIPE™ Framework to two health campaigns addressing vaccine hesitancy in underserved communities. Exposure to inaccurate/misleading health information impacts vaccination adoption, especially for individuals with low health/digital literacy. Underserved groups-like minority, racial/ethnic, or rural populations-typically have lower literacy and higher rates of vaccine hesitancy. Grounded in persuasion and behavioral change theory, the Health Information Persuasion Exploration (HIPE™) Framework was applied to the Black/Haitian community in Miami-Dade, Florida and the Migrant Agricultural Worker Community in Central Valley, California. The campaigns addressed each community's unique characteristics via Detect, Analyze, Design, and Evaluate phases of the HIPE framework. Both campaigns achieved their respective vaccine uptake goals. For Miami-Dade, over 850 vaccinations were administered (the goal was 800 vaccinations), and vaccination rates increased by 25.22%. In Central Valley, vaccination rates for 5-11-year-old children in Merced and Stanislaus counties increased about 20% and 14%, respectively, and overall vaccination rates increased compared to surrounding counties. Discussion of the results and recommendations for future research highlight the potential efficacy of applying the HIPE™ Framework for developing health campaigns and response strategies to improve health outcomes.

Intervention studies to encourage HPV vaccination using narrative: A scoping review

OBJECTIVE

This review aimed to provide an overview of intervention studies that aimed to encourage HPV vaccination using narratives.

METHODS

We searched MEDLINE, CINAHL, PsycINFO, and PsycARTICLES for English language articles that quantitatively examined the persuasive effect of narratives on encouraging HPV vaccination through interventions.

RESULTS

A total of 25 studies were identified. Most studies were conducted in the United States of America, adopted a convenient sampling of university students, measured vaccination intention as the primary outcome, and used text messages in the interventions. A minority of the studies measured vaccination behavior and examined the long-term effects of persuasion. Narratives were as effective as didactics and statistics in encouraging HPV vaccination in most included studies. The findings were mixed or scarce for the effect of combining narratives and statistics, and the person (the first vs. third), narrator, framing, and content of narratives.

CONCLUSION

More findings from a broader range of well-designed studies are needed to determine which narratives can encourage HPV vaccination across different populations.

PRACTICE IMPLICATIONS

Findings indicated using narratives can be a part of repertoire of messages encouraging HPV vaccination.

Localizing COVID-19 Misinformation: A Case Study of Tracking Twitter Pandemic Narratives in Pennsylvania Using Computational Network Science

The recent COVID-19 outbreak has highlighted the importance of effective communication strategies to control the spread of the virus and debunk misinformation. By using accurate narratives, both online and offline, we can motivate communities to follow preventive measures and shape attitudes toward them. However, the abundance of misinformation stories can lead to vaccine hesitancy, obstructing the timely implementation of preventive measures, such as vaccination. Therefore, it is crucial to create appropriate and community-centered solutions based on regional data analysis to address mis/disinformation narratives and implement effective countermeasures specific to the particular geographic area.In this case study, we have attempted to create a research pipeline to analyze local narratives on social media, particularly Twitter, to identify misinformation spread locally, using the state of Pennsylvania as an example. Our proposed methodology pipeline identifies main communication trends and misinformation stories for the major cities and counties in southwestern PA, aiming to assist local health officials and public health specialists in instantly addressing pandemic communication issues, including misinformation narratives. Additionally, we investigated anti-vax actors' strategies in promoting harmful narratives. Our pipeline includes data collection, Twitter influencer analysis, Louvain clustering, BEND maneuver analysis, bot identification, and vaccine stance detection. Public health organizations and community-centered entities can implement this data-driven approach to health communication to inform their pandemic strategies.

Public discourse and debate about vaccines in the midst of the covid-19 pandemic: a qualitative content analysis of Twitter

Objectives

Characterize the public debate and discourse about vaccines during the covid-19 vaccination programmes.

Methods

We performed a manual content analysis of a sample of English-written Twitter posts that included the word vaccine and its derivatives. We categorized 7 variables pertaining to the content of the posts, and classified the type of user that published the post and the number of retweets. Then, the patterns of association between these variables were further explored.

Results

Among the tweets with negative tone towards vaccines, 33% display negationist discourses, 29% protest or defiance discourses, 13% discuss the pandemic management measures and yet another 13% of these tweets display a scientific discourse. Research results, vaccination data and practical information are more associated to positive tone towards vaccines, while news relate to neutral tone. The users that received more retweets were media accounts and journalists, followed by government accounts and scientific organizations related to the government. Tweets displaying preventive messages received more retweets in average. The discourses most associated with objective information are the preventive, institutional, medical-scientific, and those about the different measures to manage the pandemic. On the other hand, the most subjective tweets are those with negationist, antinegationist and protest discourses.

Conclusions

Although there is a non-negligible proportion of tweets that are directly opposed to vaccines, also an important part of vaccine-negative content takes the form of protest discourses, criticisms towards government actions as well as towards the measures to tackle the pandemic. Therefore, negative discourses during the pandemic included serious vaccine hesitancy cases. Moreover, they were not only fuelled by distrust in science, but also and very importantly they were connected to dissatisfaction towards the public management of the pandemic.

Quantified multidimensional public sentiment characteristics on social media for public opinion management: Evidence from the COVID-19 pandemic

Background

Public sentiments arising from public opinion communication pose a serious psychological risk to public and interfere the communication of nonpharmacological intervention information during the COVID-19 pandemic. Problems caused by public sentiments need to be timely addressed and resolved to support public opinion management.

Objective

This study aims to investigate the quantified multidimensional public sentiments characteristics for helping solve the public sentiments issues and strengthen public opinion management.

Methods

This study collected the user interaction data from the Weibo platform, including 73,604 Weibo posts and 1,811,703 Weibo comments. Deep learning based on pretraining model, topics clustering and correlation analysis were used to conduct quantitative analysis on time series characteristics, content-based characteristics and audience response characteristics of public sentiments in public opinion during the pandemic.

Results

The research findings were as follows: first, public sentiments erupted after priming, and the time series of public sentiments had window periods. Second, public sentiments were related to public discussion topics. The more negative the audience sentiments were, the more deeply the public participated in public discussions. Third, audience sentiments were independent of Weibo posts and user attributes, the steering role of opinion leaders was invalid in changing audience sentiments.

Discussion

Since the COVID-19 pandemic, there has been an increasing demand for public opinion management on social media. Our study on the quantified multidimensional public sentiments characteristics is one of the methodological contributions to reinforce public opinion management from a practical perspective.

Applications of Social Media and Digital Technologies in COVID-19 Vaccination: Scoping Review

BACKGROUND

Social media and digital technologies have played essential roles in disseminating information and promoting vaccination during the COVID-19 pandemic. There is a need to summarize the applications and analytical techniques of social media and digital technologies in monitoring vaccine attitudes and administering COVID-19 vaccines.

OBJECTIVE

We aimed to synthesize the global evidence on the applications of social media and digital technologies in COVID-19 vaccination and to explore their avenues to promote COVID-19 vaccination.

METHODS

We searched 6 databases (PubMed, Scopus, Web of Science, Embase, EBSCO, and IEEE Xplore) for English-language articles from December 2019 to August 2022. The search terms covered keywords relating to social media, digital technology, and COVID-19 vaccines. Articles were included if they provided original descriptions of applications of social media or digital health technologies/solutions in COVID-19 vaccination. Conference abstracts, editorials, letters, commentaries, correspondence articles, study protocols, and reviews were excluded. A modified version of the Appraisal Tool for Cross-Sectional Studies (AXIS tool) was used to evaluate the quality of social media-related studies. The review was undertaken with the guidance of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews.

RESULTS

A total of 178 articles were included in our review, including 114 social media articles and 64 digital technology articles. Social media has been applied for sentiment/emotion analysis, topic analysis, behavioral analysis, dissemination and engagement analysis, and information quality analysis around COVID-19 vaccination. Of these, sentiment analysis and topic analysis were the most common, with social media data being primarily analyzed by lexicon-based and machine learning techniques. The accuracy and reliability of information on social media can seriously affect public attitudes toward COVID-19 vaccines, and misinformation often leads to vaccine hesitancy. Digital technologies have been applied to determine the COVID-19 vaccination strategy, predict the vaccination process, optimize vaccine distribution and delivery, provide safe and transparent vaccination certificates, and perform postvaccination surveillance. The applied digital technologies included algorithms, blockchain, mobile health, the Internet of Things, and other technologies, although with some barriers to their popularization.

CONCLUSIONS

The applications of social media and digital technologies in addressing COVID-19 vaccination-related issues represent an irreversible trend. Attention should be paid to the ethical issues and health inequities arising from the digital divide while applying and promoting these technologies.

Communicating COVID-19 Risk on Instagram: A Content Analysis of Official Public Health Messaging During the First Year of the Pandemic

Early in the COVID-19 pandemic, social media platform Instagram surged in popularity as a source of health information. Both the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC) leveraged Instagram accounts to publicly distribute COVID-related information. The current study investigated whether WHO and CDC messaging strategies on Instagram adhered to best practices defined by two theoretical frameworks: the extended parallel process model and crisis and emergency risk communication. We conducted a quantitative content analysis of COVID-related posts (n = 726) published between January-December 2020 to determine how both agencies (1) communicated the threat of the pandemic (e.g. susceptibility and severity of negative COVID-19 consequences); (2) appealed to self-, response, and collective efficacy; (3) incorporated cues to action (e.g. preventive behaviors, information seeking); and (4) leveraged credibility cues (e.g. scientific evidence, experts). Results showed threat information was limited, whereas efficacy appeals and cues to action were abundant. The CDC relied more heavily on depictions of self- and response efficacy, whereas the WHO appealed more frequently than the CDC to collective efficacy. Neither visually modeled behaviors nor leveraged scientific evidence or experts with great frequency. Implications for future research and official communication efforts via social media are discussed.

Futile or fertile? The effect of persuasive strategies on citizen engagement in COVID-19 vaccine-related tweets across six national health departments

National health departments across the globe have utilized persuasive strategies to promote COVID-19 vaccines through Twitter. However, the effectiveness of those strategies is unclear. This study thereby examined how national health departments deployed persuasive strategies to promote citizen engagement in COVID-19 vaccine-related tweets in six countries, including the UK, the US, Germany, Japan, South Korea, and India. Guided by the heuristic-systematic model and the health belief model, we found that national health departments differed significantly in the use of systematic-heuristic cues and health belief constructs in COVID-19 vaccine-related tweets. Generally, the provision of scientific information and appeals to anecdotes and fear positively, while appeals to bandwagon negatively, predicted citizen engagement. Messages about overcoming barriers and promoting vaccine benefits and self-efficacy positively affected engagement. Emphases of COVID-19 threats and cues to vaccinate demonstrated negative impacts. Importantly, health departments across countries often used futile or detrimental strategies in tweets. A locally adapted evidence-based approach for COVID-19 vaccination persuasion was discussed.

Filipinos' COVID-19 vaccine hesitancy comments in TikTok videos: A manifest content analysis

OBJECTIVES

Vaccine hesitancy is one of the top 10 threats to world health. The ongoing pandemic highlighted this health threat. The COVID-19 vaccine hesitancy remains underreported in the Philippines. Thus, this study aimed to describe and analyze the comments of Filipinos in TikTok videos about COVID-19 vaccine hesitancy.

DESIGN

Manifest content analysis.

SAMPLE

A total of 25 TikTok videos and their comments (n = 4564) were analyzed.

METHODS

We collected data between July 2021 and October 2021. Bengtsson's approach to content analysis was utilized to analyze the data. Data were validated using member-checking and intercoder reliability.

RESULTS

This study afforded three themes of COVID-19 vaccine hesitancy: (a) fear and mistrust (subthemes: influence of Dengvaxia vaccine, the influence of people who refuse to be vaccinated, lack of trust in the government, lack of trust in healthcare workers, doubts on vaccines' effectiveness), (b) misinformation and disinformation (subthemes: misbeliefs, insufficient knowledge), and (c) adamant attitudes (subthemes: unwillingness to be vaccinated, picky on vaccine brand).

CONCLUSION

Our study established Filipinos' diverse reasons for COVID-19 vaccine hesitancy. TikTok, as a social media platform, is used for COVID-19 vaccine discussions and the dissemination of misinformation. To prepare for the next pandemic or public health disaster, the government, HCWs, and the public must efficiently convey timely, accurate health information and dispel misinformation on social media platforms.

How to counter the anti-vaccine rhetoric: Filling information voids and building resilience

Widely circulating anti-vaccine misinformation online has been constituting a large obstacle for the success of COVID-19 vaccination campaigns and for the well-being of people during the pandemic. In this paper we discuss strategies to mitigate negative effects of online anti-vaccine contents on public health and to prevent hesitant individuals from falling prey of the traps set by anti-vaccine disinformation spreaders. Here we discuss the importance of filling information voids and understanding trends and concerns that shape the vaccine debate, and we highlight the relevance of building resilience to vaccine misinformation by strengthening public health and digital literacy.

Covid-19 vaccines in Italian public opinion: Identifying key issues using Twitter and Natural Language Processing

The COVID-19 pandemic has changed society and people's lives. The vaccination campaign started December 27th 2020 in Italy, together with most countries in the European Union. Social media platforms can offer relevant information about how citizens have experienced and perceived the availability of vaccines and the start of the vaccination campaign. This study aims to use machine learning methods to extract sentiments and topics relating to COVID-19 vaccination from Twitter. Between February and May 2021, we collected over 71,000 tweets containing vaccines-related keywords from Italian Twitter users. To get the dominant sentiment throughout the Italian population, spatial and temporal sentiment analysis was performed using VADER, highlighting sentiment fluctuations strongly influenced by news of vaccines' side effects. Additionally, we investigated the opinions of Italians with respect to different vaccine brands. As a result, 'Oxford-AstraZeneca' vaccine was the least appreciated among people. The application of the Dynamic Latent Dirichlet Allocation (DLDA) model revealed three fundamental topics, which remained stable over time: vaccination plan info, usefulness of vaccinating and concerns about vaccines (risks, side effects and safety). To the best of our current knowledge, this one the first study on Twitter to identify opinions about COVID-19 vaccination in Italy and their progression over the first months of the vaccination campaign. Our results can help policymakers and research communities track public attitudes towards COVID-19 vaccines and help them make decisions to promote the vaccination campaign.

Discussions About COVID-19 Vaccination on Twitter in Turkey: Sentiment Analysis

OBJECTIVES

The present study aims to examine coronavirus disease 2019 (COVID-19) vaccination discussions on Twitter in Turkey and conduct sentiment analysis.

METHODS

The current study performed sentiment analysis of Twitter data with the artificial intelligence (AI) Natural Language Processing (NLP) method. The tweets were retrieved retrospectively from March 10, 2020, when the first COVID-19 case was seen in Turkey, to April 18, 2022. A total of 10,308 tweets accessed. The data were filtered before analysis due to excessive noise. First, the text is tokenized. Many steps were applied in normalizing texts. Tweets about the COVID-19 vaccines were classified according to basic emotion categories using sentiment analysis. The resulting dataset was used for training and testing ML (ML) classifiers.

RESULTS

It was determined that 7.50% of the tweeters had positive, 0.59% negative, and 91.91% neutral opinions about the COVID-19 vaccination. When the accuracy values of the ML algorithms used in this study were examined, it was seen that the XGBoost (XGB) algorithm had higher scores.

CONCLUSIONS

Three of 4 tweets consist of negative and neutral emotions. The responsibility of professional chambers and the public is essential in transforming these neutral and negative feelings into positive ones.

How Media Literacy, Trust of Experts and Flu Vaccine Behaviors Associated with COVID-19 Vaccine Intentions

PURPOSE

To assess how previous experiences and new information contributed to COVID-19 vaccine intentions.

DESIGN

Online survey (N = 1264) with quality checks.

SETTING

Cross-sectional U.S. survey fielded June 22-July 18, 2020.

SAMPLE

U.S. residents 18+; quotas reflecting U.S. Census, limited to English speakers participating in internet panels.

MEASURES

Media literacy for news content and sources, COVID-19 knowledge; perceived usefulness of health experts; if received flu vaccine in past 12 months; vaccine willingness scale; demographics.

ANALYSIS

Structural equation modelling.

RESULTS

Perceived usefulness of health experts (b = .422, P < .001) and media literacy (b = .162, P < .003) predicted most variance in vaccine intentions (R-squared=31.5%). A significant interaction (b = .163, P < .001) between knowledge (b = -.132, P = .052) and getting flu shot (b = .185, P < .001) predicted additional 3.5% of the variance in future vaccine intentions. An increase in knowledge of COVID-19 associated with a decrease in vaccine intention among those declining the flu shot.

CONCLUSION

The interaction result suggests COVID-19 knowledge had a positive association with vaccine intention for flu shot recipients but a counter-productive association for those declining it. Media literacy and trust in health experts provided strong counterbalancing influences. Survey-based findings are correlational; thus, predictions are based on theory. Future research should study these relationships with panel data or experimental designs.

A Health Crisis in the Age of Misinformation: How Social Media and Mass Media Influenced Misperceptions about COVID-19 and Compliance Behavior

The media are important information disseminators in society. Particularly in uncertain times, such as the COVID-19 pandemic, citizens are very "media dependent." The way in which people are informed about the coronavirus heavily depends on the type of media they use. Especially on social media, the share of misinformation is considerable, which might impact the way in which people comply with preventive measures. Our study investigates how media use affects misperceptions about the coronavirus and whether this influences important behavioral determinants as well as compliance behavior itself. The results of a unique 5-wave panel survey (N = 1,741) conducted between April 2020 and October 2020 show that the use of mass media reduces misperceptions. The same was found for Twitter users, whereas Facebook and Instagram users have more misperceptions about the coronavirus. Misperceptions negatively influence the perceived severity, susceptibility and efficacy of preventive measures taken by governments, which may ultimately result in decreased compliance. Our findings underline the important role of media consumption and misperceptions in shaping citizens' beliefs and behavior regarding COVID-19. They re-emphasize the importance of mass media, such as newspapers, television broadcasts or reliable news websites, to inform the public about current affairs. They also imply that platform media might be more heterogeneous in their effects than mass media.

Communication Is Not a Virus: COVID-19 Vaccine-Critical Activity on Facebook and Implications for the 'Infodemic' Concept

In February 2020 the World Health Organization declared an 'infodemic' in relation to COVID-19. The label infers that people are being contaminated by 'misinformation' as they would be by a virus. However, this metaphor conveys a simplistic empirical understanding of communication, which may encourage 'information control' responses. This article argues for the importance of understanding the diverse factors that impact the effectiveness of communication - including the context in which it is received, and the emergent properties created through communication processes. Analyzing 'vaccine-critical' Facebook activity in Australia between 1 December 2020 and 28 February 2022, we find that controlling access to or censoring vaccine-critical misinformation does not lead to a reduction in vaccine-critical narratives. Rather, discussions continue based on more tenable political and social arguments. Further, bans antagonize vaccine-critical Facebook users and encourage them to move to other platforms where they may be radicalized. Crucially, recruitment to vaccine-critical sites accelerated following both bans of 'misinformation' and the introduction of vaccine mandates, suggesting that such responses can lead to increased discontentment. Accordingly, we call for researchers, policy makers and media platforms to engage with a more nuanced view of communication, acknowledging the powerful role of audiences' uses and gratifications in determining the effectiveness of public health messaging.

Bots' Activity on COVID-19 Pro and Anti-Vaccination Networks: Analysis of Spanish-Written Messages on Twitter

This study aims to analyze the role of bots in the dissemination of health information, both in favor of and opposing vaccination against COVID-19. Study design: An observational, retrospective, time-limited study was proposed, in which activity on the social network Twitter was analyzed. Methods: Data related to pro-vaccination and anti-vaccination networks were compiled from 24 December 2020 to 30 April 2021 and analyzed using the software NodeXL and Botometer. The analyzed tweets were written in Spanish, including keywords that allow identifying the message and focusing on bots’ activity and their influence on both networks. Results: In the pro-vaccination network, 404 bots were found (14.31% of the total number of users), located mainly in Chile (37.87%) and Spain (14.36%). The anti-vaccination network bots represented 16.19% of the total users and were mainly located in Spain (8.09%) and Argentina (6.25%). The pro-vaccination bots generated greater impact than bots in the anti-vaccination network (p < 0.000). With respect to the bots’ influence, the pro-vaccination network did have a significant influence compared to the activity of human users (p < 0.000). Conclusions: This study provides information on bots’ activity in pro- and anti-vaccination networks in Spanish, within the context of the COVID-19 pandemic on Twitter. It is found that bots in the pro-vaccination network influence the dissemination of the pro-vaccination message, as opposed to those in the anti-vaccination network. We consider that this information could provide guidance on how to enhance the dissemination of public health campaigns, but also to combat the spread of health misinformation on social media.

Infodemic and fake news - A comprehensive overview of its global magnitude during the COVID-19 pandemic in 2021: A scoping review

The spread of fake news increased dramatically during the COVID-19 pandemic worldwide. This study aims to synthesize the extant literature to understand the magnitude of this phenomenon in the wake of the pandemic in 2021, focusing on the motives and sociodemographic profiles, Artificial Intelligence (AI)-based tools developed, and the top trending topics related to fake news. A scoping review was adopted targeting articles published in five academic databases (January 2021-November 2021), resulting in 97 papers. Most of the studies were empirical in nature (N = 69) targeting the general population (N = 26) and social media users (N = 13), followed by AI-based detection tools (N = 27). Top motives for fake news sharing include low awareness, knowledge, and health/media literacy, Entertainment/Pass Time/Socialization, Altruism, and low trust in government/news media, whilst the phenomenon was more prominent among those with low education, males and younger. Machine and deep learning emerged to be the widely explored techniques in detecting fake news, whereas top topics were related to vaccine, virus, cures/remedies, treatment, and prevention. Immediate intervention and prevention efforts are needed to curb this anti-social behavior considering the world is still struggling to contain the spread of the COVID-19 virus.

Attitudes toward COVID-19 Vaccination on Social Media: A Cross-Platform Analysis

During the COVID-19 pandemic, social media content analysis allowed for tracking attitudes toward newly introduced vaccines. However, current evidence is limited to single social media platforms. Our objective was to compare arguments used by anti-vaxxers in the context of COVID-19 vaccines across Facebook, Twitter, Instagram, and TikTok. We obtained the data set of 53,671 comments regarding COVID-19 vaccination published between August 2021 and February 2022. After that, we established categories of anti-vaccine content, manually classified comments, and compared the frequency of occurrence of the categories between social media platforms. We found that anti-vaxxers on social media use 14 categories of arguments against COVID-19 vaccines. The frequency of these categories varies across different social media platforms. The anti-vaxxers' activity on Facebook and Twitter is similar, focusing mainly on distrust of government and allegations regarding vaccination safety and effectiveness. Anti-vaxxers on TikTok mainly focus on personal freedom, while Instagram users encouraging vaccination often face criticism suggesting that vaccination is a private matter that should not be shared. Due to the differences in vaccine sentiment among users of different social media platforms, future research and educational campaigns should consider these distinctions, focusing more on the platforms popular among adolescents (i.e., Instagram and TikTok).

Narrative communication regarding the Covid-19 vaccine: a thematic analysis of comments on Romanian official Facebook page “RO Vaccinare”

As of October 2021, Romania is one of the world’s most affected countries by Covid-19 pandemic, and this occurs on the background of a very slow rate of vaccination. Drawing on the sociology of storytelling, this article highlights various narratives that make the vaccination campaign in Romania difficult. Based on a case study on Romanian official vaccination page “RO Vaccinare,” a thematic analysis on six official narratives and subsequent 137 comments post on the official page highlighted both pro-vaccination narratives and anti-vaccination narratives. The two main narratives reflect different persuasive strategies, so the role of communication experts is vital in avoiding other further mis/disinformation. For example, pro-vaccination narratives repeatedly call for education as the most important variable, given that the detachment from conspiracy theories requires a certain level of socialization in this regard. In addition, the ‘science versus religion’ dichotomy is frequently discussed, with religion being seen as an obstacle to awareness of the role of a vaccination campaign. On the other hand, the motivations invoked in the anti-vaccination narratives discuss the vaccine as an ‘experimental serum,’ while the doctors who administer it are considered ‘killers.’ Also, some of the narratives in this category consider religion to be above science in terms of public health.

A comprehensive examination of association between belief in vaccine misinformation and vaccination intention in the COVID-19 context

Misinformation about COVID-19 vaccines is widely available in the public communication environment. Exposure to the misinformation may increase perceived risk of and evoke negative emotions toward COVID-19 vaccines that may eventually reduce COVID-19 vaccination intentions. The negative influences of misinformation may vary by aspects of individuals' social networks. Expanding the reasoned action approach, we proposed a comprehensive model to examine the roles of misinformation beliefs, perceived risk, fear, worry, and social networks in explaining COVID-19 vaccination intentions. We tested the model using survey data of South Korean adults, collected when the Korean government launched its nationwide vaccination program in April 2021 (n = 744). The results from our step-by-step path analyses indicated that COVID-19 vaccination intentions had positive direct associations with vaccination-specific factors such as attitudes toward, injunctive norms on, and perceived behavioral control over COVID-19 vaccination. Perceived risk was also directly linked to intentions. Among these factors, attitudes and injunctive norms were most strongly related to intentions. Misinformation beliefs and worry had negative indirect relationships with intentions via the mediation of these variables directly connected to intentions. The negative influences of misinformation beliefs were greater among respondents reported stronger tie strengths. Theoretical and practical implications were discussed.

Encouraging COVID-19 vaccination via an evolutionary theoretical approach: A randomized controlled study in Japan

OBJECTIVE

We aimed to examine the effect of a message that target the fundamental human motive of kin care on COVID-19 vaccination recommendations among participants with young children, based on an evolutionary theoretical approach.

METHODS

Participants with young children (n = 969) were randomly assigned either to a group that received an intervention message that targeted the fundamental motive of kin care, or that targeted the fundamental motive of disease avoidance, or a control message. Intention to receive COVID-19 vaccination was assessed both before and after reading the messages. A one-way ANOVA with Tukey's or Games-Howell test was conducted.

RESULTS

An intervention message targeting the fundamental motive of kin care and disease avoidance significantly increased intention of vaccination versus a control message (p < 0.001, respectively).

CONCLUSION

The evolutionary theoretical approach that focuses on fundamental human motives has the potential to extend the communication strategy for COVID-19 vaccination recommendations.

PRACTICE IMPLICATIONS

Health professionals should deliver messages that target the fundamental motive of kin care as well as messages about the susceptibility and severity of COVID-19 and vaccine efficacy (e.g., "Get vaccinated against COVID-19 for your child's sake, because if you are infected, you will be unable to care for your child.").

Social media and attitudes towards a COVID-19 vaccination: A systematic review of the literature

BACKGROUND

Vaccine hesitancy continues to limit global efforts in combatting the COVID-19 pandemic. Emerging research demonstrates the role of social media in disseminating information and potentially influencing people's attitudes towards public health campaigns. This systematic review sought to synthesize the current evidence regarding the potential role of social media in shaping COVID-19 vaccination attitudes, and to explore its potential for shaping public health interventions to address the issue of vaccine hesitancy.

METHODS

We performed a systematic review of the studies published from inception to 13 of March2022 by searching PubMed, Web of Science, Embase, PsychNET, Scopus, CINAHL, and MEDLINE. Studies that reported outcomes related to coronavirus disease 2019 (COVID-19) vaccine (attitudes, opinion, etc.) gathered from the social media platforms, and those analyzing the relationship between social media use and COVID-19 hesitancy/acceptance were included. Studies that reported no outcome of interest or analyzed data from sources other than social media (websites, newspapers, etc.) will be excluded. The Newcastle Ottawa Scale (NOS) was used to assess the quality of all cross-sectional studies included in this review. This study is registered with PROSPERO (CRD42021283219).

FINDINGS

Of the 2539 records identified, a total of 156 articles fully met the inclusion criteria. Overall, the quality of the cross-sectional studies was moderate - 2 studies received 10 stars, 5 studies received 9 stars, 9 studies were evaluated with 8, 12 studies with 7,16 studies with 6, 11 studies with 5, and 6 studies with 4 stars. The included studies were categorized into four categories. Cross-sectional studies reporting the association between reliance on social media and vaccine intentions mainly observed a negative relationship. Studies that performed thematic analyses of extracted social media data, mainly observed a domination of vaccine hesitant topics. Studies that explored the degree of polarization of specific social media contents related to COVID-19 vaccines observed a similar degree of content for both positive and negative tone posted on different social media platforms. Finally, studies that explored the fluctuations of vaccination attitudes/opinions gathered from social media identified specific events as significant cofactors that affect and shape vaccination intentions of individuals.

INTERPRETATION

This thorough examination of the various roles social media can play in disseminating information to the public, as well as how individuals behave on social media in the context of public health events, articulates the potential of social media as a platform of public health intervention to address vaccine hesitancy.

FUNDING

None.

Encouraging HPV Vaccination via an Evolutionary Theoretical Approach: A Randomized Controlled Study in Japan

In recent years, researchers have discussed the introduction of an evolutionary perspective into public health and health behavior research. We aimed to examine the effects of messages that target the fundamental human motive of kin care on HPV vaccination recommendations among mothers with daughters, based on an evolutionary theoretical approach. This study consisted of a three-arm parallel-group single-blinded randomized controlled study. A web-based survey was conducted from 7 to 8 October 2021 in Japan. Mothers with daughters (n = 969) were randomly assigned either to a group that received an intervention message that targeted the fundamental motive of kin care, or that targeted the fundamental motive of disease avoidance, or a control message. Intention to have daughter(s) receive HPV vaccination was assessed both before and right after reading the messages. A one-way ANOVA with Tukey’s or Games−Howell test was conducted. An intervention message targeting the fundamental motive of kin care and disease avoidance significantly increased intention of vaccination versus a control message (p < 0.001, respectively). There was no significant difference between the two intervention groups. The evolutionary theoretical approach that focuses on fundamental human motives may have the potential to extend the communication strategy for HPV vaccination recommendations. Health professionals may be recommended to deliver messages that target the fundamental motive of kin care as well as messages about the susceptibility and severity of cervical cancer and vaccine efficacy (e.g., “Getting cervical cancer can prevent childbirth. To protect your daughter and your future grandchildren, get your daughter vaccinated against HPV”). However, the present study only evaluated HPV vaccination intentions in Japanese mothers with daughters. Future studies should evaluate vaccination behavior in a wider range of subjects to confirm that the evolutionary theoretical approach promotes HPV vaccination.

Mis-Dis Information in COVID-19 Health Crisis: A Narrative Review

Background: In this narrative review, we address the COVID-19 pandemic mis–dis information crisis in which healthcare systems have been pushed to their limits, with collapses occurring worldwide. The context of uncertainty has resulted in skepticism, confusion, and general malaise among the population. Informing the public has been one of the major challenges during this pandemic. Misinformation is defined as false information shared by people who have no intention of misleading others. Disinformation is defined as false information deliberately created and disseminated with malicious intentions. Objective: To reach a consensus and critical review about mis–dis information in COVID-19 crisis. Methods: A database search was conducted in PsychINFO, MedLine (Pubmed), Cochrane (Wiley), Embase and CinAhl. Databases used the MeSH-compliant keywords of COVID-19, 2019-nCoV, Coronavirus 2019, SARS-CoV-2, misinformation, disinformation, information, vaccines, vaccination, origin, target, spread, communication. Results: Both misinformation and disinformation can affect the population’s confidence in vaccines (development, safety, and efficacy of vaccines, as well as denial of the severity of SARS-CoV infection). Institutions should take into account that a great part of the success of the intervention to combat a pandemic has a relationship with the power to stop the misinformation and disinformation processes. The response should be well-structured and addressed from different key points: central level and community level, with official and centralized communication channels. The approach should be multifactorial and enhanced by the collaboration of social media companies to stop misleading information, and trustworthy people both working or not working in the health care systems to boost the power of the message. Conclusions: The response should be well-structured and addressed from different key points: central level and community level, with official and clearly centralized communication channels. The approach should be multifactorial and enhanced from the collaboration of social media companies to stop misleading information, and trustworthy people both working and not working in the health care systems to boost the power of a message based on scientific evidence.

Clustering based sentiment analysis on Twitter data for COVID-19 vaccines in India

Coronavirus is a new and rapidly spreading viral disease. It is essential to have a vaccine in order to reduce the virus's impact. Vaccination-related sentiments can influence an individual's decision to accept the vaccines. Evaluating the sentiments is a time-consuming and challenging process. Sentiment analysis (SA) could have an impact on the vaccination initiatives as well as changes in people's opinions and behaviour around immunizations. Since social media is widely utilized to disseminate information, mining this data is a popular area of study these days. On Twitter, a wide range of opinions about the negative effects of licensed vaccines have been expressed over time. In this research, tweets are gathered, pre-processed to remove extraneous data, and then utilized for sentiments analysis utilizing the Lexicons-based technique and machine learning. After feature extraction, the clustering is performed using MEEM approach. This research proposed a Clustering Based Twitter sentiments analysis of COVID 19 (C-SAT COVID 19) vaccinations in India. An enhanced random forest classifier is implemented in this research to classify the sentiment scores provided by the sentiment analysis. A classification is performed based on the negative, neutral, and positive  sentiment analysis to examine people's emotions towards vaccinations accessible in India. 

Anxiety and covid-19 compliance behaviors in the UK: The moderating role of conspiratorial thinking

The Covid-19 pandemic raised many societal problems, one of them being convincing people to comply with government measures to control its spread. In the UK, many unprecedented measures were taken to that end. Public health bodies often use fear appeals to encourage people to obey the rules. What happens though when individuals hold beliefs contrary to government narrative? In this study, the relationship between coronavirus induced anxiety and compliance behavior over the first UK lockdown is examined in relation to general conspiratorial beliefs and specific Covid-19 conspiracy myths. Results suggest a small interaction between specific Covid-19 conspiracy beliefs and anxiety, and that while for most, increased anxiety enforces compliance, for those with conspiratorial beliefs regarding Covid-19 (but not general conspiratorial beliefs), this may not be true. Fear appeals may be successful for the majority, but a small minority may continue to ignore advice. Implications for public health are discussed.

Immunity Debt or Vaccination Crisis? A Multi-Method Evidence on Vaccine Acceptance and Media Framing for Emerging COVID-19 Variants

Renewed COVID-19 outbreaks, stemming from the highly infectious Delta and Omicron variants, prompted rising fears of a ‘pandemic among the unvaccinated’. To address this prevalent vaccination crisis, media framing communication strategies can amplify the scientific evidence on COVID-19 vaccines to reach diverse geographic and socio-economic communities. The critical role of media framing strategies to engage and encourage large populations regarding vaccine acceptance has been rarely studied, despite growing evidence on vaccine hesitancy. The present study used a multi-method approach (i.e., content analysis and quasi-experiments) that unpacked the framing practices employed by the mainstream media in Pakistan. The findings of the content analysis revealed that the media extensively used uncertainty, conflict, consequences, and action rather than new evidence and reassurance frames in its COVID-19 related campaigns. In a series of quasi-experiments involving 720 participants, we manipulated these six frames of COVID-19 related news coverage (i.e., uncertainty, conflict, consequences, action, new evidence, and reassurance) to investigate the underlying mechanism that influences vaccine acceptance. The findings established that the message-consistent effects of media frames manifesting fear (e.g., consequence and uncertainty) and action cues made receivers more supportive of vaccination. The present study findings theoretically address the calls for a more inclusive “community-health reporting model”, besides offering new evidence on the media framing strategies to deliver more targeted, meaningful, and effective campaigns to raise public acceptance for COVID-19 vaccines.

Gulf Countries’ Citizens’ Acceptance of COVID-19 Vaccines—A Machine Learning Approach

The COVID-19 pandemic created a global emergency in many sectors. The spread of the disease can be subdued through timely vaccination. The COVID-19 vaccination process in various countries is ongoing and is slowing down due to multiple factors. Many studies on European countries and the USA have been conducted and have highlighted the public’s concern that over-vaccination results in slowing the vaccination rate. Similarly, we analyzed a collection of data from the gulf countries’ citizens’ COVID-19 vaccine-related discourse shared on social media websites, mainly via Twitter. The people’s feedback regarding different types of vaccines needs to be considered to increase the vaccination process. In this paper, the concerns of Gulf countries’ people are highlighted to lessen the vaccine hesitancy. The proposed approach emphasizes the Gulf region-specific concerns related to COVID-19 vaccination accurately using machine learning (ML)-based methods. The collected data were filtered and tokenized to analyze the sentiments extracted using three different methods: Ratio, TextBlob, and VADER methods. The sentiment-scored data were classified into positive and negative tweeted data using a proposed LSTM method. Subsequently, to obtain more confidence in classification, the in-depth features from the proposed LSTM were extracted and given to four different ML classifiers. The ratio, TextBlob, and VADER sentiment scores were separately provided to LSTM and four machine learning classifiers. The VADER sentiment scores had the best classification results using fine-KNN and Ensemble boost with 94.01% classification accuracy. Given the improved accuracy, the proposed scheme is robust and confident in classifying and determining sentiments in Twitter discourse.

The Association Between Dissemination and Characteristics of Pro-/Anti-COVID-19 Vaccine Messages on Twitter: Application of the Elaboration Likelihood Model

Background

Messages on one's stance toward vaccination on microblogging sites may affect the reader's decision on whether to receive a vaccine. Understanding the dissemination of provaccine and antivaccine messages relating to COVID-19 on social media is crucial; however, studies on this topic have remained limited.

Objective

This study applies the elaboration likelihood model (ELM) to explore the characteristics of vaccine stance messages that may appeal to Twitter users. First, we examined the associations between the characteristics of vaccine stance tweets and the likelihood and number of retweets. Second, we identified the relative importance of the central and peripheral routes in decision-making on sharing a message.

Methods

English-language tweets from the United States that contained provaccine and antivaccine hashtags (N=150,338) were analyzed between April 26 and August 26, 2021. Logistic and generalized negative binomial regressions were conducted to predict retweet outcomes. The content-related central-route predictors were measured using the numbers of hashtags and mentions, emotional valence, emotional intensity, and concreteness. The content-unrelated peripheral-route predictors were measured using the numbers of likes and followers and whether the source was a verified user.

Results

Content-related characteristics played a prominent role in shaping decisions regarding whether to retweet antivaccine messages. Particularly, positive valence (incidence rate ratio [IRR]=1.32, P=.03) and concreteness (odds ratio [OR]=1.17, P=.01) were associated with higher numbers and likelihood of retweets of antivaccine messages, respectively; emotional intensity (subjectivity) was associated with fewer retweets of antivaccine messages (OR=0.78, P=.03; IRR=0.80, P=.04). However, these factors had either no or only small effects on the sharing of provaccine tweets. Retweets of provaccine messages were primarily determined by content-unrelated characteristics, such as the numbers of likes (OR=2.55, IRR=2.24, P<.001) and followers (OR=1.31, IRR=1.28, P<.001).

Conclusions

The dissemination of antivaccine messages is associated with both content-related and content-unrelated characteristics. By contrast, the dissemination of provaccine messages is primarily driven by content-unrelated characteristics. These findings signify the importance of leveraging the peripheral route to promote the dissemination of provaccine messages. Because antivaccine tweets with positive emotions, objective content, and concrete words are more likely to be disseminated, policymakers should pay attention to antivaccine messages with such characteristics.

Topics and Sentiments of Public Concerns Regarding COVID-19 Vaccines: Social Media Trend Analysis

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.