Content Themes and Influential Voices Within Vaccine Opposition on Twitter, 2019

Leveraging Media Monitoring to Inform Targeted Health Communications for Adolescents, Older Adults, and LGBTQ+ People

OBJECTIVE

This manuscript assesses how media monitoring can guide the tailoring of public health communications for adolescents, older adults, and LGBTQ+ individuals, addressing their unique mental health challenges.

DESIGN

The study employed a thematic analysis of publicly available digital and social media data.

SETTING

Research was conducted using media monitoring platforms, with a focus on conversations relevant to specific groups within the United States.

PARTICIPANTS

The dataset included millions of public posts relevant to mental health issues among adolescents, older adults, and LGBTQ+ communities, collected over a one-year period. Main Outcome Measures: Key themes and patterns within mental health discussions were identified.

RESULTS

Discussions around the "youth mental health crisis" were prominent, with 25% of adolescent-related posts reflecting this sentiment, often highlighting the impact of social media and academic pressures. For older adults, themes of loneliness and financial struggles were recurrent, with discussions showing a lack of practical support and resources. In LGBTQ+ conversations, there was an emphasis on the challenges of discrimination and identity-related misconceptions, with 28% of the mentions relating to mental health crises involving suicide or self-harm. These discussions underscored the critical need for inclusive and affirmative support tailored to the unique challenges faced by these groups.

CONCLUSIONS

Media monitoring provides essential insights that can improve public health messaging by identifying trending mental health discussions and sentiments. By acknowledging and addressing the specific needs and challenges of specific population groups, public health communicators can develop more effective strategies that not only highlight problems but also offer clear, actionable solutions to promote better mental health outcomes and support. This approach is crucial for adapting health communications to the evolving landscape of media and public discourse, ensuring that messages are both relevant and supportive.

Discovering why people believe disinformation about healthcare

Disinformation-false information intended to cause harm or for profit-is pervasive. While disinformation exists in several domains, one area with great potential for personal harm from disinformation is healthcare. The amount of disinformation about health issues on social media has grown dramatically over the past several years, particularly in response to the COVID-19 pandemic. The study described in this paper sought to determine the characteristics of multimedia social network posts that lead them to believe and potentially act on healthcare disinformation. The study was conducted in a neuroscience laboratory in early 2022. Twenty-six study participants each viewed a series of 20 either honest or dishonest social media posts, dealing with various aspects of healthcare. They were asked to determine if the posts were true or false and then to provide the reasoning behind their choices. Participant gaze was captured through eye tracking technology and investigated through "area of interest" analysis. This approach has the potential to discover the elements of disinformation that help convince the viewer a given post is true. Participants detected the true nature of the posts they were exposed to 69% of the time. Overall, the source of the post, whether its claims seemed reasonable, and the look and feel of the post were the most important reasons they cited for determining whether it was true or false. Based on the eye tracking data collected, the factors most associated with successfully detecting disinformation were the total number of fixations on key words and the total number of revisits to source information. The findings suggest the outlines of generalizations about why people believe online disinformation, suggesting a basis for the development of mid-range theory.

A social media intervention for communicating vaccine safety in low- and middle-income countries: protocol for a pilot study

Vaccine safety is a concern that continues to drive hesitancy and refusal in populations in low-and-middle income countries (LMICs). Communicating about vaccine safety is a strategy that can successfully change personal and community perceptions and behaviors toward vaccination. The COVID-19 infodemic emergency with the rapid rollout of new vaccines and new technology, demonstrated the need for good and effective vaccine safety communication. The Vaccine Safety Net (VSN), a WHO-led global network of websites that provide reliable information on vaccine safety offers the ideal environment for gathering web and social media analytics for measuring impact of vaccine safety messages. Its members work with a wide range of populations, in different geographic locations and at many levels including national, regional, and local. We propose to undertake a pilot study to evaluate the feasibility of implementing COVID-19 vaccine safety communications with VSN members working in LMICs and to assess the impact of communications on public knowledge, attitudes, and perceptions.

Understanding COVID-19 vaccine hesitancy in Canada

While Canada has had relatively high vaccination rates against COVID-19, specifically during earlier waves of the pandemic, vaccine hesitancy has continued to serve as a significant barrier to adequate protection against the virus and, more recently, booster vaccine uptake. This paper explores the processes underlying Canadians' perceptions of COVID-19 vaccines and their decisions to take or refuse them, as well as how public policy and health messaging about vaccination has influenced vaccination attitudes and behaviors. Our focus group interviews with 18 vaccinated and unvaccinated adult Canadians conducted during October 2021 reveal that, in some respects, COVID-19 vaccine hesitancy conforms to prior knowledge about some of the factors that affect vaccine attitudes (e.g., the influence of known medical providers) but deviates from current theoretical frameworks regarding general vaccine hesitancy. Specifically, these frameworks emphasize a lack of scientific knowledge and literacy ("knowledge deficit" accounts) or individuals' inability to incorporate rational risk perceptions into initial emotional responses to vaccines ("emotionality/irrationality" accounts). In contrast to the knowledge deficit account, we find that expressions of COVID-19 vaccine hesitancy were most frequently associated with an information surplus or inability to prioritize information from multiple and often contradictory sources. Furthermore, top-down pro-vaccination messaging often triggered significant pushback against what participants perceived as moral shaming of the unvaccinated. Our findings demonstrate the necessity for a new framework to understand and address vaccine hesitancy. A better theoretical account of vaccine hesitancy has important implications for future vaccination efforts, specifically within the context of new variants and low booster vaccination rates in Canada.

A taxonomy of anti-vaccination arguments from a systematic literature review and text modelling

The proliferation of anti-vaccination arguments is a threat to the success of many immunization programmes. Effective rebuttal of contrarian arguments requires an approach that goes beyond addressing flaws in the arguments, by also considering the attitude roots-that is, the underlying psychological attributes driving a person's belief-of opposition to vaccines. Here, through a pre-registered systematic literature review of 152 scientific articles and thematic analysis of anti-vaccination arguments, we developed a hierarchical taxonomy that relates common arguments and themes to 11 attitude roots that explain why an individual might express opposition to vaccination. We further validated our taxonomy on coronavirus disease 2019 anti-vaccination misinformation, through a combination of human coding and machine learning using natural language processing algorithms. Overall, the taxonomy serves as a theoretical framework to link expressed opposition of vaccines to their underlying psychological processes. This enables future work to develop targeted rebuttals and other interventions that address the underlying motives of anti-vaccination arguments.

A multi-site intervention using influencers to communicate about syringe service programmes

Introduction

In the USA, syringe services programmes (SSPs) provide a range of harm reduction services and have numerous benefits for communities. However, stigma, misconceptions about SSPs and changing policies/legislation remain a challenge to effective implementation. This study reviews the implementation of two digital interventions, Appalachian Influence and Shared Influence, which used social media influencers and digital volunteers to communicate positive information about harm reduction and SSPs.

Methods

The intervention was designed to deliver accurate and supportive messaging in locally relevant and meaningful ways. Messaging was informed by interviews with subject matter experts and community organisations, and was integrated into prompts used by local influencers (paid individuals with more than 1,000 followers) and digital volunteers (unpaid individuals with no following requirement, who joined the project independently).

Results

In the first 6 months of implementation, Appalachian Influence and Shared Influence engaged a total of 9,014 individuals, 236 of whom were paid influencers and 8,778 of whom were digital volunteers. Paid influencer posts achieved a total of 868,943 impressions, 42,432 engagements and 1,567 comments. Comments on paid influencer posts were overwhelmingly positive, with 87.4% positive and 0.8% negative. Interviews showed the importance of understanding local realities, leading with compassion and emphasising the 'human' aspects of dependency and addiction in messaging.

Conclusion

This study shows the potential to implement an influencer-led social media intervention to reach people with authentic and compassionate messaging about harm reduction and SSPs. Future research should examine intervention effectiveness and how this approach can be applied to other stigmatised topics.

Visualizing the Interpretation of a Criteria-Driven System That Automatically Evaluates the Quality of Health News: Exploratory Study of 2 Approaches

BACKGROUND

Machine learning techniques have been shown to be efficient in identifying health misinformation, but the results may not be trusted unless they can be justified in a way that is understandable.

OBJECTIVE

This study aimed to provide a new criteria-based system to assess and justify health news quality. Using a subset of an existing set of criteria, this study compared the feasibility of 2 alternative methods for adding interpretability. Both methods used classification and highlighting to visualize sentence-level evidence.

METHODS

A total of 3 out of 10 well-established criteria were chosen for experimentation, namely whether the health news discussed the costs of the intervention (the cost criterion), explained or quantified the harms of the intervention (the harm criterion), and identified the conflicts of interest (the conflict criterion). The first step of the experiment was to automate the evaluation of the 3 criteria by developing a sentence-level classifier. We tested Logistic Regression, Naive Bayes, Support Vector Machine, and Random Forest algorithms. Next, we compared the 2 visualization approaches. For the first approach, we calculated word feature weights, which explained how classification models distill keywords that contribute to the prediction; then, using the local interpretable model-agnostic explanation framework, we selected keywords associated with the classified criterion at the document level; and finally, the system selected and highlighted sentences with keywords. For the second approach, we extracted sentences that provided evidence to support the evaluation result from 100 health news articles; based on these results, we trained a typology classification model at the sentence level; and then, the system highlighted a positive sentence instance for the result justification. The number of sentences to highlight was determined by a preset threshold empirically determined using the average accuracy.

RESULTS

The automatic evaluation of health news on the cost, harm, and conflict criteria achieved average area under the curve scores of 0.88, 0.76, and 0.73, respectively, after 50 repetitions of 10-fold cross-validation. We found that both approaches could successfully visualize the interpretation of the system but that the performance of the 2 approaches varied by criterion and highlighting the accuracy decreased as the number of highlighted sentences increased. When the threshold accuracy was ≥75%, this resulted in a visualization with a variable length ranging from 1 to 6 sentences.

CONCLUSIONS

We provided 2 approaches to interpret criteria-based health news evaluation models tested on 3 criteria. This method incorporated rule-based and statistical machine learning approaches. The results suggested that one might visually interpret an automatic criterion-based health news quality evaluation successfully using either approach; however, larger differences may arise when multiple quality-related criteria are considered. This study can increase public trust in computerized health information evaluation.

A Multifaceted Campaign to Combat COVID-19 Misinformation in the Hispanic Community

At the height of the COVID-19 pandemic, the Public Good Projects, Hispanic Communications Network and World Voices Media joined forces to launch a nationwide, multifaceted campaign which aimed to increase vaccine confidence and decrease misinformation on social media within Hispanic communities. We created a Spanish vaccine misinformation tracking system to detect and assess misinformation circulating in online Spanish conversations. We used our media monitoring findings to work with Hispanic social media (SM) influencers, volunteers, and celebrities to spread pro-vaccine messaging online. We created misinformation-responsive SM assets, newsletters, talking points and trainings for Hispanic-serving community-based organizations (CBOs) to help them respond to misinformation and increase vaccine uptake. We used our misinformation findings to inform the creation of mass media communications such as radio PSAs and op-eds. In Year 1, our new Spanish monitoring system captured and organized 35 M Spanish and 212.7 M English posts about COVID-19 misinformation. We recruited 496 paid influencers, 2 Hispanic celebrities and 1,034 digital volunteers. We sent 70 newsletters to an average of 1539 CBO subscribers, containing 206 talking points and 344 resources (SM assets, toolkits, videos) in English and Spanish to support their outreach. Our radio PSAs reached 26.9 M people and the op-eds reached 2.9 M people. This project shows the proliferation of misinformation circulating in online Spanish conversations. It also shows we were effective at reaching our target audience with fact-based COVID-19 misinformation prebunk and debunk messaging.

Multilayer hybrid ensemble machine learning model for analysis of Covid-19 vaccine sentiments

This work presents the analysis of significant sentiments and attitudes of people towards the COVID-19 vaccination. The tweeter messages related to the COVID-19 vaccine is used for sentiment evaluation in this work. The proposed work consists of two steps: (i) natural processing language (NLP) and (ii) classification. The NLP is utilized for text pre-processing, tokenization, data labelling, and feature extraction. Further, a stack-based ensemble machine learning model is used to classify sentiments as positive, negative, or neutral. The stack ensemble machine learning model includes seven heterogeneous machine learning techniques namely, Naive Bayes, Logistic regression, Decision Tree, Random Forest, AdaBoost Classifier, Gradient Boosting, and extreme Gradient Boosting (XGB). The highest classification accuracy of 97.2%, 88.34%, 88.22%, 85.23%, 86.30%, 87.54%, 86.63%, and 88.78% is achieved by ensemble machine learning model, Logistic regression, AdaBoost, Decision Tree, Naive Bayes, Random Forest, Gradient Boosting, and XGB Classifier, respectively.

COVID-19 Vaccine Hesitancy, Acceptance, and Promotion Among Healthcare Workers: A Mixed-Methods Analysis

Even with vaccine mandates, COVID-19 vaccine hesitancy remains a concern among healthcare workers, in part due to their role in promoting vaccination among patients and communities. To examine COVID-19 vaccine hesitancy, acceptance, and promotion among healthcare workers, we conducted a mixed-methods analysis of (1) survey responses about COVID-19 vaccination and (2) Twitter messages (i.e., tweets) relevant to COVID-19 vaccination and healthcare. A total of 540 hospital employees completed the survey. Those that completed less than 80% of the survey or did not endorse employment at the hospital were excluded, resulting in a total of 511 valid responses; 93.2% reported receiving at least one dose of a COVID-19 vaccine. Approximately 1/3 of vaccinated individuals indicated they posted about receiving the vaccine on social media. Simultaneously, we analyzed a sample of 3845 tweets; 2299 (60%) were relevant to COVID-19 vaccination and 1863 (81%) were coded as authored by an individual. Of tweets authored by an individual, 6% (n = 106) were authored by a healthcare provider/health sciences student. Among relevant tweets, the most frequent code across all sentiment categories was related to the pharmaceutical industry (n = 529 tweets, 28%; n = 33, 31% of tweets authored by healthcare workers). Triangulation of results found themes including vaccine access, trust, and vaccine safety or negative health impacts. Results suggest that promoting the sharing of COVID-19 vaccine personal narratives on social media, combined with interventions targeting specific reasons for COVID-19 vaccine hesitancy and emphasizing freedom from fear once vaccinated could be effective at reducing COVID-19 vaccine hesitancy among this population.

Digital Marketing: A Unique Multidisciplinary Approach towards the Elimination of Viral Hepatitis

New technologies are supported by the global implementation of the internet. These improvements have deeply affected various disciplines of sciences and consequently changed services such as daily business, particularly health sectors. Innovative digital marketing strategies utilize the channels of social media and retrieved user data to analyze and improve relevant services. These multidisciplinary innovations can assist specialists, physicians and researchers in diagnostic, prophylaxis and treatment issues in the health sector. Accordingly, compared to recent decades, health decision makers are more accurate and trustful in defining new strategies. Interestingly, using social media and mobile health apps in current pandemics of SARS-CoV-2 could be an important instance of the key role of these platforms at the local and global level of health policies. These digital technologies provide platforms to connect public health sectors and health politicians for communicating and spreading relevant information. Adding influencers and campaigns to this toolbox strengthens the implementation of public health programs. In 2016, the WHO adopted a global program to eliminate viral hepatitis by 2030. Recent constructive measures that have been used in the battle against COVID-19 could be adopted for the elimination of viral hepatitis program. The presented evidence in our narrative review demonstrates that the application of digital marketing tools to create campaigns on social media, armed with professional influencers, can efficiently consolidate this program. The application of different strategies in using these popular tools will raise the public awareness about viral hepatitis. Subsequently, the availability of an effective vaccine for HBV and antiviral medication for HCV can motivate the audience to take steps towards prophylaxis and screening methods against these infectious illnesses. The encouragement of health policy makers to apply digital communication technologies and comprehensive roadmaps to implement this global program will certainly decrease the burden of viral hepatitis worldwide.

Exploring Coronavirus Disease 2019 Vaccine Hesitancy on Twitter Using Sentiment Analysis and Natural Language Processing Algorithms

BACKGROUND

Vaccination can help control the coronavirus disease 2019 (COVID-19) pandemic but is undermined by vaccine hesitancy. Social media disseminates information and misinformation regarding vaccination. Tracking and analyzing social media vaccine sentiment could better prepare health professionals for vaccination conversations and campaigns.

METHODS

A real-time big data analytics framework was developed using natural language processing sentiment analysis, a form of artificial intelligence. The framework ingests, processes, and analyzes tweets for sentiment and content themes, such as natural health or personal freedom, in real time. A later dataset evaluated the relationship between Twitter sentiment scores and vaccination rates in the United States.

RESULTS

The real-time analytics framework showed a widening gap in sentiment with more negative sentiment after vaccine rollout. After rollout, using a static dataset, an increase in positive sentiment was followed by an increase in vaccination. Lag cross-correlation analysis across US regions showed evidence that once all adults were eligible for vaccination, the sentiment score consistently correlated with vaccination rate with a lag of around 1 week. The Granger causality test further demonstrated that tweet sentiment scores may help predict vaccination rates.

CONCLUSIONS

Social media has influenced the COVID-19 response through valuable information and misinformation and distrust. This tool was used to collect and analyze tweets at scale in real time to study sentiment and key terms of interest. Separate tweet analysis showed that vaccination rates tracked regionally with Twitter vaccine sentiment and might forecast changes in vaccine uptake and/or guide targeted social media and vaccination strategies. Further work is needed to analyze the interplay between specific populations, vaccine sentiment, and vaccination rates.

#DoctorsSpeakUp: Exploration of Hashtag Hijacking by Anti-Vaccine Advocates and the Influence of Scientific Counterpublics on Twitter

The #DoctorsSpeakUp hashtag, which was designed by physicians to collectively promote vaccines on Twitter in Spring of 2020, was hijacked by anti-vaccine advocates. Through the lens of counterpublic sphere theory, thematic analysis revealed that the hashtag hijacking by a scientific counterpublic was successful, and the majority of #DoctorsSpeakUp tweets were oriented against vaccines. Five overarching themes emerged in anti-vaccine hijacked tweets, including: personal experience with vaccine injury, profits over people, lack of liability, perception that doctors are uninformed, and 'We are the Herd.' In contrast, fewer than 17% of tweets originated from pro-vaccine doctors who openly identified themselves as such in their tweets or profiles. Thus, using the #DoctorsSpeakUp hashtag, anti-vaccine advocates dominated the discourse, which speaks to the communication dynamics afforded within the information ecosystem of a social network. Hashtag activism can connect individuals and promote grassroots movements but may also backfire, allowing a vocal minority of individuals to shout the loudest through the digital megaphone.

Positive attitudes towards COVID-19 vaccines: A cross-country analysis

COVID-19 severely impacted world health and, as a consequence of the measures implemented to stop the spread of the virus, also irreversibly damaged the world economy. Research shows that receiving the COVID-19 vaccine is the most successful measure to combat the virus and could also address its indirect consequences. However, vaccine hesitancy is growing worldwide and the WHO names this hesitancy as one of the top ten threats to global health. This study investigates the trend in positive attitudes towards vaccines across ten countries since a positive attitude is important. Furthermore, we investigate those variables related to having a positive attitude, as these factors could potentially increase the uptake of vaccines. We derive our text corpus from vaccine-related tweets, harvested in real-time from Twitter. Using Natural Language Processing (NLP), we derive the sentiment and emotions contained in the tweets to construct daily time-series data. We analyse a panel dataset spanning both the Northern and Southern hemispheres from 1 February 2021 to 31 July 2021. To determine the relationship between several variables and the positive sentiment (attitude) towards vaccines, we run various models, including POLS, Panel Fixed Effects and Instrumental Variables estimations. Our results show that more information about vaccines' safety and the expected side effects are needed to increase positive attitudes towards vaccines. Additionally, government procurement and the vaccine rollout should improve. Accessibility to the vaccine should be a priority, and a collective effort should be made to increase positive messaging about the vaccine, especially on social media. The results of this study contribute to the understanding of the emotional challenges associated with vaccine uptake and inform policymakers, health workers, and stakeholders who communicate to the public during infectious disease outbreaks. Additionally, the global fight against COVID-19 might be lost if the attitude towards vaccines is not improved.

Vaccine Hesitancy and Anti-Vaccination Attitudes during the Start of COVID-19 Vaccination Program: A Content Analysis on Twitter Data

Twitter is a useful source for detecting anti-vaccine content due to the increasing prevalence of these arguments on social media. We aimed to identify the prominent themes about vaccine hesitancy and refusal on social media posts in Turkish during the COVID-19 pandemic. In this qualitative study, we collected public tweets (n = 551,245) that contained a vaccine-related keyword and had been published between 9 December 2020 and 8 January 2021 through the Twitter API. A random sample of tweets (n = 1041) was selected and analyzed by four researchers with the content analysis method. We found that 90.5% of the tweets were about vaccines, 22.6% (n = 213) of the tweets mentioned at least one COVID-19 vaccine by name, and the most frequently mentioned COVID-19 vaccine was CoronaVac (51.2%). We found that 22.0% (n = 207) of the tweets included at least one anti-vaccination theme. Poor scientific processes (21.7%), conspiracy theories (16.4%), and suspicions towards manufacturers (15.5%) were the most frequently mentioned themes. The most co-occurring themes were “poor scientific process” with “suspicion towards manufacturers” (n = 9), and “suspicion towards health authorities” (n = 5). This study may be helpful for health managers, assisting them to identify the major concerns of the population and organize preventive measures through the significant role of social media in early spread of information about vaccine hesitancy and anti-vaccination attitudes.

Social-Cyber Maneuvers Analysis During the COVID-19 Vaccine Initial Rollout

BACKGROUND

During the time surrounding the approval and initial distribution of Pfizer-BioNTech's COVID-19 vaccine, large numbers of social media users took to used their platforms to voice opinions on the vaccine. They formed pro- and anti-vaccination groups towards the purpose of influencing behaviors to vaccinate or not to vaccinate. The methods of persuasion and manipulation for convincing audiences online can be characterized under a framework for social-cyber maneuvers known as the BEND maneuvers. Previous studies have been conducted on the spread of COVID-19 vaccine disinformation. However, these previous studies lacked comparative analyses over time on both community stances and the competing techniques of manipulating both the narrative and network structure to persuade target audiences.

OBJECTIVE

This study aimed to understand community response to vaccination by dividing Twitter data from the initial Pfizer-BioNTech COVID-19 vaccine rollout into pro-vaccine and anti-vaccine stances, identifying key actors and groups, and evaluating how the different communities use social-cyber maneuvers, or BEND maneuvers, to influence their target audiences and the network as a whole.

METHODS

COVID-19 Twitter vaccine data was collected using the Twitter API for one-week periods before, during, and six weeks after the initial Pfizer-BioNTech rollout (December 2020-January 2021). Bot identifications and linguistic cues were derived for users and tweets, respectively, to use as metrics for evaluating social-cyber maneuvers. ORA-PRO software was then used to separate the vaccine data into pro-vaccine and anti-vaccine communities and to facilitate identification of key actors, groups, and BEND maneuvers for a comparative analysis between each community and the entire network.

RESULTS

Both the pro-vaccine and anti-vaccine communities used combinations of the 16 BEND maneuvers to persuade their target audiences of their particular stances. Our analysis showed how each side attempted to build its own community while simultaneously narrowing and neglecting the opposing community. Pro-vaccine users primarily used positive maneuvers such as excite and explain messages to encourage vaccination and backed leaders within their group. In contrast, anti-vaccine users relied on negative maneuvers to dismay and distort messages with narratives on side effects and death and attempted to neutralize the effectiveness of the leaders within the pro-vaccine community. Furthermore, nuking through platform policies showed to be effective in reducing the size of the anti-vaccine online community and the quantity of anti-vaccine messages.

CONCLUSIONS

Social media continues to be a domain for manipulating beliefs and ideas. These conversations can ultimately lead to real-world actions such as to vaccinate or not to vaccinate against COVID-19. Moreover, social media policies should be further explored as an effective means for curbing disinformation and misinformation online.

CLINICALTRIAL

Not applicable.

Public Opinion and Sentiment Before and at the Beginning of COVID-19 Vaccinations in Japan: Twitter Analysis

Background

COVID-19 vaccines are considered one of the most effective ways for containing the COVID-19 pandemic, but Japan lagged behind other countries in vaccination in the early stages. A deeper understanding of the slow progress of vaccination in Japan can be instructive for COVID-19 booster vaccination and vaccinations during future pandemics.

Objective

This retrospective study aims to analyze the slow progress of early-stage vaccination in Japan by exploring opinions and sentiment toward the COVID-19 vaccine in Japanese tweets before and at the beginning of vaccination.

Methods

We collected 144,101 Japanese tweets containing COVID-19 vaccine-related keywords between August 1, 2020, and June 30, 2021. We visualized the trend of the tweets and sentiments and identified the critical events that may have triggered the surges. Correlations between sentiments and the daily infection, death, and vaccination cases were calculated. The latent dirichlet allocation model was applied to identify topics of negative tweets from the beginning of vaccination. We also conducted an analysis of vaccine brands (Pfizer, Moderna, AstraZeneca) approved in Japan.

Results

The daily number of tweets continued with accelerating growth after the start of large-scale vaccinations in Japan. The sentiments of around 85% of the tweets were neutral, and negative sentiment overwhelmed the positive sentiment in the other tweets. We identified 6 public-concerned topics related to the negative sentiment at the beginning of the vaccination process. Among the vaccines from the 3 manufacturers, the attitude toward Moderna was the most positive, and the attitude toward AstraZeneca was the most negative.

Conclusions

Negative sentiment toward vaccines dominated positive sentiment in Japan, and the concerns about side effects might have outweighed fears of infection at the beginning of the vaccination process. Topic modeling on negative tweets indicated that the government and policy makers should take prompt actions in building a safe and convenient vaccine reservation and rollout system, which requires both flexibility of the medical care system and the acceleration of digitalization in Japan. The public showed different attitudes toward vaccine brands. Policy makers should provide more evidence about the effectiveness and safety of vaccines and rebut fake news to build vaccine confidence.

Human Papillomavirus Vaccination and Social Media: Results in a Trial With Mothers of Daughters Aged 14-17

Introduction: Parents acquire information about human papillomavirus (HPV) vaccines online and encounter vaccine-critical content, especially on social media, which may depress vaccine uptake. Secondary analysis in a randomized trial of a Facebook-delivered adolescent health campaign targeting mothers with posts on HPV vaccination was undertaken with the aims of (a) determining whether the pre–post-change occurred in self-reports of the mothers on HPV vaccination of their adolescent daughters; (b) describing the comments and reactions to vaccine posts; (c) exploring the relationship of campaign engagement of the mothers assessed by their comments and reactions to posts to change in the self-reports of the mothers of HPV vaccination.

Materials and Methods: Mothers of daughters aged 14–17 were recruited from 34 states of the US (n = 869). A social media campaign was delivered in two Facebook private groups that differed in that 16% of posts in one were focused on indoor tanning (IT) and 16% in the other, on prescription drug misuse, assigned by randomization. In both groups, posts promoted HPV vaccination (n = 38 posts; no randomization) and vaccination for other disease (e.g., influenza, n = 49). HPV and other vaccination posts covered the need for a vaccine, the number of adolescents vaccinated, how vaccines are decreasing the infection rates, and stories of positive benefits of being vaccinated or harms from not vaccinating. Guided by social cognitive theory and diffusion of innovations theory, posts were intended to increase knowledge, perceived risk, response efficacy (i.e., a relative advantage over not vaccinated daughters), and norms for vaccination. Some vaccination posts linked to stories to capitalize on identification effects in narratives, as explained in transportation theory. All mothers received the posts on vaccination (i.e., there was no randomization). Mothers completed surveys at baseline and 12- and 18-month follow-up to assess HPV vaccine uptake by self-report measures. Reactions (such as sad, angry) and comments to each HPV-related post were counted and coded.

Results: Initiation of HPV vaccination (1 dose) was reported by 63.4% of mothers at baseline, 71.3% at 12-month posttest (pre/post p < 0.001), and 73.3% at 18-month posttest (pre/post p < 0.001). Completion of HPV vaccination (two or three doses) was conveyed by 50.2% of mothers at baseline, 62.5% at 12-month posttest (pre/post p < 0.001), and 65.9% at 18-month posttest (pre/post p < 0.001). For posts on HPV vaccines, 8.1% of mothers reacted (n = 162 total), and 68.4% of posts received a reaction (63.2% like; 13.2% love, 7.9% sad). In addition, 7.6% of mothers commented (n = 122; 51 unfavorable, 68 favorable, 1 neutral), and 50.0% of these posts received a comment. There were no differences in pre–post change in vaccine status by the count of reactions or comments to HPV vaccine posts (Ps > 0.05). Baseline vaccination was associated with the valence of comments to HPV vaccine posts (7.2% of mothers whose daughters had completed the HPV series at baseline made a favorable comment but 7.6% of mothers whose daughters were unvaccinated made an unfavorable comment).

Conclusion: Effective strategies are needed in social media to promote HPV vaccines and counter misinformation about and resistance to them. Mothers whose daughters complete the HPV vaccine course might be recruited as influencers on HPV vaccines, as they may be predisposed to talk favorably about the vaccine. Comments from mothers who have not been vaccinated should be monitored to ensure that they do not spread vaccine-critical misinformation. Study limitations included lack of randomization and control group, relatively small number of messages on HPV vaccines, long measurement intervals, inability to measure views of vaccination posts, reduced generalizability related to ethnicity and social media use, and use of self-reported vaccine status.

Clinical Trial Registration:www.clinicaltrials.gov, identifier NCT02835807.

Social media influencers can be used to deliver positive information about the flu vaccine: findings from a multi-year study

Large-scale digital flu vaccine campaigns have experienced difficulty increasing vaccination coverage among African Americans and Hispanics, and are routinely inundated by negative responses from vaccine opponents. A digital campaign employing user-generated content from social media 'micro' influencers who are predominantly followed by African Americans and Hispanics was implemented during the 2018-19 and 2019-20 flu seasons to disseminate positive information about the flu vaccine. At the time, this constituted the largest influencer-driven health campaign focused on these communities in the United States. Comments on posts were qualitatively coded to determine content perceptions among those exposed to posts. Digital metrics were also analyzed. During Year 1, posts reached 9 million+ social media users and generated 64 612 likes or shares, and 1512 responses. In Year 2, posts reached 8 million+ users and generated 155 600 likes or shares, and 3122 responses. Around 94% of public responses to posts were positive, suggesting this is a promising strategy to communicate health information and could shift social norms, particularly for heavily debated topics such as vaccination. This strategy represents a more community-led and participatory approach than most large-scale vaccination campaigns have attempted, with immediate applicability to communications about the COVID-19 vaccine.

An analysis of COVID-19 vaccine sentiments and opinions on Twitter

OBJECTIVE

We identified public sentiments and opinions toward the COVID-19 vaccines based on the content of Twitter.

MATERIALS AND METHODS

We retrieved 4,552,652 publicly available tweets posted within the timeline of January 2020 to January 2021. Following extraction, we identified vaccine sentiments and opinions of tweets and compared their progression by time, geographical distribution, main themes, keywords, posts engagement metrics and accounts characteristics.

RESULTS

We found a slight difference in the prevalence of positive and negative sentiments, with positive being the dominant polarity and having higher engagements. The amount of discussion on vaccine rejection and hesitancy was more than interest in vaccines during the course of the study, but the pattern was different in various countries. We found the accounts producing vaccine opposition content were partly Twitter bots or political activists while well-known individuals and organizations generated the content in favour of vaccination.

CONCLUSION

Understanding sentiments and opinions toward vaccination using Twitter may help public health agencies to increase positive messaging and eliminate opposing messages in order to enhance vaccine uptake.

Correcting HPV Vaccination Misinformation Online: Evaluating the HPV Vaccination NOW Social Media Campaign

The human papillomavirus (HPV) vaccine provides protection from six HPV-related cancers. Approximately half of South Carolina adolescents have not completed the vaccination series, representing a missed opportunity to prevent cancer. The HPV Vaccination NOW: This is Our Moment social media campaign is an initiative of the South Carolina Cancer Alliance (SCCA) and Hollings Cancer Center at the Medical University of South Carolina (MUSC). This statewide social media campaign aimed to increase parental awareness of and build vaccine confidence around HPV vaccination in S.C. The ten-week campaign was strategically implemented between June and August 2019 to encourage HPV vaccination at back-to-school medical appointments. A process evaluation showed that the campaign resulted in over 370,000 total impressions, reached over 33,000 individuals, and culminated with over 1122 followers. There were over 2700 engagements on Facebook and Twitter. A qualitative content analysis indicated that pro-vaccine and anti-vaccine comments were dominated by personal stories. Comments promoting misinformation about the HPV vaccine were often countered through peer-to-peer dialogue. Findings suggest that creating opportunities for the target audience to engage with campaign messages effectively corrected misinformation.