Automatically Appraising the Credibility of Vaccine-Related Web Pages Shared on Social Media: A Twitter Surveillance Study

Sexual and Gender-Diverse Individuals Face More Health Challenges during COVID-19: A Large-Scale Social Media Analysis with Natural Language Processing

Background: The COVID-19 pandemic has caused a disproportionate impact on the sexual and gender-diverse (SGD) community. Compared with non-SGD populations, their social relations and health status are more vulnerable, whereas public health data regarding SGD are scarce. Methods: To analyze the concerns and health status of SGD individuals, this cohort study leveraged 471,371,477 tweets from 251,455 SGD and 22,644,411 non-SGD users, spanning from 2020 February 1 to 2022 April 30. The outcome measures comprised the distribution and dynamics of COVID-related topics, attitudes toward vaccines, and the prevalence of symptoms. Results: Topic analysis revealed that SGD users engaged more frequently in discussions related to "friends and family" (20.5% vs. 13.1%, P < 0.001) and "wear masks" (10.1% vs. 8.3%, P < 0.001) compared to non-SGD users. Additionally, SGD users exhibited a marked higher proportion of positive sentiment in tweets about vaccines, including Moderna, Pfizer, AstraZeneca, and Johnson & Johnson. Among 102,464 users who self-reported COVID-19 diagnoses, SGD users disclosed significantly higher frequencies of mentioning 61 out of 69 COVID-related symptoms than non-SGD users, encompassing both physical and mental health challenges. Conclusion: The results provide insights into an understanding of the unique needs and experiences of the SGD community during the pandemic, emphasizing the value of social media data in epidemiological and public health research.

The Role of Scientific Research in Human Papillomavirus Vaccine Discussions on Twitter: Social Network Analysis

BACKGROUND

Attitudes toward the human papillomavirus (HPV) vaccine and accuracy of information shared about this topic in web-based settings vary widely. As real-time, global exposure to web-based discourse about HPV immunization shapes the attitudes of people toward vaccination, the spread of misinformation and misrepresentation of scientific knowledge contribute to vaccine hesitancy.

OBJECTIVE

In this study, we aimed to better understand the type and quality of scientific research shared on Twitter (recently rebranded as X) by vaccine-hesitant and vaccine-confident communities.

METHODS

To analyze the use of scientific research on social media, we collected tweets and retweets using a list of keywords associated with HPV and HPV vaccines using the Academic Research Product Track application programming interface from January 2019 to May 2021. From this data set, we identified tweets referring to or sharing scientific literature through a Boolean search for any tweets with embedded links, hashtags, or keywords associated with scientific papers. First, we used social network analysis to build a retweet or reply network to identify the clusters of users belonging to either the vaccine-confident or vaccine-hesitant communities. Second, we thematically assessed all shared papers based on typology of evidence. Finally, we compared the quality of research evidence and bibliometrics between the shared papers in the vaccine-confident and vaccine-hesitant communities.

RESULTS

We extracted 250 unique scientific papers (including peer-reviewed papers, preprints, and gray literature) from approximately 1 million English-language tweets. Social network maps were generated for the vaccine-confident and vaccine-hesitant communities sharing scientific research on Twitter. Vaccine-hesitant communities share fewer scientific papers; yet, these are more broadly disseminated despite being published in less prestigious journals compared to those shared by the vaccine-confident community.

CONCLUSIONS

Vaccine-hesitant communities have adopted communication tools traditionally wielded by health promotion communities. Vaccine-confident communities would benefit from a more cohesive communication strategy to communicate their messages more widely and effectively.

Trust in information sources as a moderator of the impact of COVID-19 anxiety and exposure to information on conspiracy thinking and misinformation beliefs: a multilevel study

This study investigates the intricate relationship between exposure to information sources, trust in these sources, conspiracy and misinformation beliefs, and COVID-19 anxiety among 509 Omani citizens aged 11 to 50, representing 11 governorates. Employing structural equation modeling, we not only examine these associations but also explore how trust and COVID-19 anxiety act as moderating variables in this context. Additionally, we delve into demographic factors such as age group, educational level, gender, and place of residence (governorate) to discern potential variations.Our findings reveal that trust in health experts is inversely related to belief in conspiracy theories, while trust in health experts negatively correlates with exposure to conspiracy and misinformation. Intriguingly, trust in health experts exhibits divergent effects across governorates: it diminishes conspiracy and misinformation beliefs in some regions but not in others. Exposure to personal contacts and digital media, on the other hand, is associated with heightened beliefs in misinformation and conspiracy theories, respectively, in select governorates. These distinctions may be attributed to proximity to Muscat, the capital city of Oman, where various media outlets and policy-making institutions are situated. Furthermore, lower educational attainment is linked to greater belief in conspiracy and misinformation. Females reported higher levels of conspiracy theory beliefs and COVID-19 anxiety while no significant differences were detected in misinformation beliefs.This study sheds light on the intricate dynamics of misinformation and conspiracy theories in the context of COVID-19 in Oman, highlighting the pivotal roles of trust and COVID-19 anxiety as moderating factors. These findings offer valuable insights into understanding and addressing the spread of misinformation and conspiracy theories during a public health crisis.

Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis

BACKGROUND

On December 20, 2019, the US "Tobacco 21" law raised the minimum legal sales age of tobacco products to 21 years. Initial research suggests that misinformation about Tobacco 21 circulated via news sources on Twitter and that sentiment about the law was associated with particular types of tobacco products and included discussions about other age-related behaviors. However, underlying themes about this sentiment as well as temporal trends leading up to enactment of the law have not been explored.

OBJECTIVE

This study sought to examine (1) sentiment (pro-, anti-, and neutral policy) about Tobacco 21 on Twitter and (2) volume patterns (number of tweets) of Twitter discussions leading up to the enactment of the federal law.

METHODS

We collected tweets related to Tobacco 21 posted between September 4, 2019, and December 31, 2019. A 2% subsample of tweets (4628/231,447) was annotated by 2 experienced, trained coders for policy-related information and sentiment. To do this, a codebook was developed using an inductive procedure that outlined the operational definitions and examples for the human coders to annotate sentiment (pro-, anti-, and neutral policy). Following the annotation of the data, the researchers used a thematic analysis to determine emergent themes per sentiment category. The data were then annotated again to capture frequencies of emergent themes. Concurrently, we examined trends in the volume of Tobacco 21-related tweets (weekly rhythms and total number of tweets over the time data were collected) and analyzed the qualitative discussions occurring at those peak times.

RESULTS

The most prevalent category of tweets related to Tobacco 21 was neutral policy (514/1113, 46.2%), followed by antipolicy (432/1113, 38.8%); 167 of 1113 (15%) were propolicy or supportive of the law. Key themes identified among neutral tweets were news reports and discussion of political figures, parties, or government involvement in general. Most discussions were generated from news sources and surfaced in the final days before enactment. Tweets opposing Tobacco 21 mentioned that the law was unfair to young audiences who were addicted to nicotine and were skeptical of the law's efficacy and importance. Methods used to evade the law were found to be represented in both neutral and antipolicy tweets. Propolicy tweets focused on the protection of youth and described the law as a sensible regulatory approach rather than a complete ban of all products or flavored products. Four spikes in daily volume were noted, 2 of which corresponded with political speeches and 2 with the preparation and passage of the legislation.

CONCLUSIONS

Understanding themes of public sentiment-as well as when Twitter activity is most active-will help public health professionals to optimize health promotion activities to increase community readiness and respond to enforcement needs including education for retailers and the general public.

Exploring 'quality' in science communication online: Expert thoughts on how to assess and promote science communication quality in digital media contexts

In recent years, the public visibility of science has greatly increased. In the digital media landscape, a wide range of players is now engaged in science communication via various online channels. While these developments offer opportunities, they also entail risks for the quality of science communication. This study explores how the quality of science communication can be assessed and promoted in the increasingly complex digital ecosystem. A two-wave survey with international science communication experts served as a basis to develop a quality framework for digital science communication and to formulate strategies to promote the quality of science communication online. Besides these outcomes, results hint at blind spots in the discourse of science communication quality that demand further investigation and reflection.

Identifying factors influencing COVID-19 vaccine uptake in Finland - a qualitative study using social media data

Introduction

Vaccine demand creation requires understanding what is driving the uptake of the vaccine. 24 Qualitative research methods are paramount to gaining a localized understanding of behavioral 25 drivers and barriers to vaccine uptake, but they are often underutilized.

Methods

This is a qualitative study that 26 used public comments on the Facebook and Twitter posts of the Finnish Institute for Health and 27 Welfare (THL) as data sources to identify behavioral drivers for COVID-19 vaccine uptake in 28 Finland. The participatory data analysis utilized thematic analysis and the Theoretical Domains 29 Framework (TDF). NVIVO was used to assist in the coding process.

Results

The greatest number of FB and 30 Twitter comments were linked with six TDF domains: knowledge, environmental context and 31 resources, beliefs in consequences, beliefs in capabilities, social and professional role, and social 32 influences. The domains included 15 themes that were interlinked. The knowledge domain 33 overlapped with all other domains.

Discussion

By using public discourse on Facebook and Twitter, and rapid 34 qualitative data analysis methods within a behavioral insight framework, this study adds to the 35 emerging knowledge about behavioral drivers of COVID-19 vaccines that can be used by public 36 health experts to enhance the uptake of vaccines during future pandemics and epidemics.

Automatic detection of health misinformation: a systematic review

The spread of health misinformation has the potential to cause serious harm to public health, from leading to vaccine hesitancy to adoption of unproven disease treatments. In addition, it could have other effects on society such as an increase in hate speech towards ethnic groups or medical experts. To counteract the sheer amount of misinformation, there is a need to use automatic detection methods. In this paper we conduct a systematic review of the computer science literature exploring text mining techniques and machine learning methods to detect health misinformation. To organize the reviewed papers, we propose a taxonomy, examine publicly available datasets, and conduct a content-based analysis to investigate analogies and differences among Covid-19 datasets and datasets related to other health domains. Finally, we describe open challenges and conclude with future directions.

Unravelling the truth: Examining the evidence for health-related claims made by naturopathic influencers on social media - a retrospective analysis

Background: Social media platforms are frequently used by the general public to access health information, including information relating to complementary and alternative medicine (CAM). The aim of this study was to measure how often naturopathic influencers make evidence-informed recommendations on Instagram, and to examine associations between the level of evidence available or presented, and user engagement. Methods: A retrospective observational study using quantitative content analysis on health-related claims made by naturopathic influencers with 30000 or more followers on Instagram was conducted. Linear regression was used to measure the association between health-related posts and the number of Likes, and Comments. Results: A total of 494 health claims were extracted from eight Instagram accounts, of which 242 (49.0%) were supported by evidence and 34 (6.9%) included a link to evidence supporting the claim. Three naturopathic influencers did not provide any evidence to support the health claims they made on Instagram. Posts with links to evidence had fewer Likes (B=-1343.9, 95% CI=-2424.4 to -263.4, X=-0.1, P=0.02) and fewer Comments (B=-82.0, 95% CI=-145.9 to -18.2, X=-0.2, P=0.01), compared to posts without links to evidence. The most common areas of health were claims relating to 'women's health' (n=94; 19.0%), and 'hair, nail and skin' (n=74; 15.0%). Conclusion: This study is one of the first to look at the evidence available to support health-related claims by naturopathic influencers on Instagram. Our findings indicate that around half of Instagram posts from popular naturopathic influencers with health claims are supported by high-quality evidence.

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.

Polarization and trust in the evolution of vaccine discourse on Twitter during COVID-19

Trust in vaccination is eroding, and attitudes about vaccination have become more polarized. This is an observational study of Twitter analyzing the impact that COVID-19 had on vaccine discourse. We identify the actors, the language they use, how their language changed, and what can explain this change. First, we find that authors cluster into several large, interpretable groups, and that the discourse was greatly affected by American partisan politics. Over the course of our study, both Republicans and Democrats entered the vaccine conversation in large numbers, forming coalitions with Antivaxxers and public health organizations, respectively. After the pandemic was officially declared, the interactions between these groups increased. Second, we show that the moral and non-moral language used by the various communities converged in interesting and informative ways. Finally, vector autoregression analysis indicates that differential responses to public health measures are likely part of what drove this convergence. Taken together, our results suggest that polarization around vaccination discourse in the context of COVID-19 was ultimately driven by a trust-first dynamic of political engagement.

Infodemic Management Using Digital Information and Knowledge Cocreation to Address COVID-19 Vaccine Hesitancy: Case Study From Ghana

Background

Infodemic management is an integral part of pandemic management. Ghana Health Services (GHS) together with the UNICEF (United Nations International Children's Emergency Fund) Country Office have developed a systematic process that effectively identifies, analyzes, and responds to COVID-19 and vaccine-related misinformation in Ghana.

Objective

This paper describes an infodemic management system workflow based on digital data collection, qualitative methodology, and human-centered systems to support the COVID-19 vaccine rollout in Ghana with examples of system implementation.

Methods

The infodemic management system was developed by the Health Promotion Division of the GHS and the UNICEF Country Office. It uses Talkwalker, a social listening software platform, to collect misinformation on the web. The methodology relies on qualitative data analysis and interpretation as well as knowledge cocreation to verify the findings.

Results

A multi-sectoral National Misinformation Task Force was established to implement and oversee the misinformation management system. Two members of the task force were responsible for carrying out the analysis. They used Talkwalker to find posts that include the keywords related to COVID-19 vaccine-related discussions. They then assessed the significance of the posts on the basis of the engagement rate and potential reach of the posts, negative sentiments, and contextual factors. The process continues by identifying misinformation within the posts, rating the risk of identified misinformation posts, and developing proposed responses to address them. The results of the analysis are shared weekly with the Misinformation Task Force for their review and verification to ensure that the risk assessment and responses are feasible, practical, and acceptable in the context of Ghana.

Conclusions

The paper describes an infodemic management system workflow in Ghana based on qualitative data synthesis that can be used to manage real-time infodemic responses.

The correlates and dynamics of COVID-19 vaccine-specific hesitancy

Most work on COVID-19 vaccine hesitancy has focused on its attitudinal and demographic correlates among individuals, but the characteristics of vaccines themselves also appear to be important. People are more willing to take vaccines with higher reported levels of efficacy and safety. Has this dynamic sparked comparative hesitancy towards specific COVID-19 vaccines? We conduct a series of cross-sectional survey experiments to test for brand-based differences in perceived effectiveness, perceived safety, and vaccination intention. Examining more than 6,200 individuals in a series of cross-sectional surveys, we find considerably more reluctance to take the AstraZeneca and Johnson & Johnson vaccines compared to those from Pfizer and Moderna if offered, despite all vaccines being approved and deemed safe and effective by a federal regulator. Comparative hesitancy towards these vaccines grew over the course of fielding as controversy arose over their link to extremely rare, but serious side effects. Comparative vaccine-specific hesitancy is strongest among people who are usually most open to mass vaccination efforts. Its effects are substantial: most respondents reported a willingness to wait months for their preferred vaccine rather than receive either the AstraZeneca or Johnson & Johnson vaccine immediately. Our findings call for additional research on the determinants and consequences of COVID-19 vaccine-specific hesitancy and communication strategies to minimize this challenge.

eHealth literacy of patients attending a primary care clinic in Malaysia and its associated factors: A cross-sectional study

BACKGROUND

People are overloaded with online health information (OHI) of variable quality. eHealth literacy is important for people to acquire and appraise reliable information to make health-related decisions. While eHealth literacy is widely studied in developed countries, few studies have been conducted among patients in low- and middle-income countries (LMICs).

OBJECTIVE

We aimed to determine the level of eHealth literacy in patients attending a primary care clinic in Malaysia and its associated factors.

METHODS

A cross-sectional study using a self-administered questionnaire was conducted in an urban primary care clinic. We used a systematic random sampling method to select patients aged 18 years and above who attended the clinic. The eHealth literacy scale (eHEALS) was used to measure eHealth literacy.

RESULTS

A total of 381 participants were included. The mean eHEALS was 24.4 ± 7.6. The eHEALS statements related to skills in appraising OHI were scored lower than statements related to looking for online resources. Higher education level of attending upper secondary school (AOR 2.53, 95% CI 1.05-6.11), tertiary education (AOR 4.05, 95% CI 1.60-10.25), higher monthly household income of >US$470 (AOR 1.95, 95% CI 1.07-3.56), and those who had sought OHI in the past month (AOR 1.95, 95% CI 1.13-3.36) were associated with a higher eHealth literacy level.

CONCLUSIONS

This study found a low eHealth literacy level among primary care patients in Malaysia. While the patients were confident in searching for OHI, they lacked skills in appraising them. Our findings inform the interventions for improving eHealth literacy in LMICs, especially educating the public about OHI appraisal.

Collective Value Promotes the Willingness to Share Pro-Vaccination Messages on Social Media in China: A Randomized Controlled Trial (Preprint)

Background

The proliferation of vaccine misinformation on social media has seriously corrupted the public’s confidence in vaccination. Proactively sharing provaccination messages on social media is a cost-effective way to enhance global vaccination rates and resist vaccine misinformation. However, few strategies for encouraging the public to proactively share vaccine-related knowledge on social media have been developed.

Objective

This research examines the effect of value type (individual vs collective) and message framing (gain vs loss) on influenza vaccination intention (experiment 1) and the willingness to share provaccination messages (experiment 2) among Chinese adults during the COVID-19 pandemic. The primary aim was to evaluate whether messages that emphasized collective value were more effective in increasing the willingness to share than messages that emphasized individual value.

Methods

We enrolled 450 Chinese adults for experiment 1 (n=250, 55.6%) and experiment 2 (n=200, 44.4%). Participants were randomly assigned to individual-gain, individual-loss, collective-gain, or collective-loss conditions with regard to the message in each experiment using the online survey platform’s randomization function. Experiment 1 also included a control group. The primary outcome was influenza vaccination intention in experiment 1 and the willingness to share provaccination messages in experiment 2.

Results

The valid sample included 213 adults in experiment 1 (females: n=151, 70.9%; mean age 29 [SD 9] years; at least some college education: n=202, 94.8%; single: n=131, 61.5%) and 171 adults in experiment 2 (females: n=106, 62.0%; mean age 28 [SD 7] years; at least some college education: n=163, 95.3%; single: n=95, 55.6%). Influenza vaccination intention was stronger in the individual-value conditions than in the collective-value conditions (F_3,166=4.96, P=.03, η²=0.03). The reverse result was found for the willingness to share provaccination messages (F_3,165=6.87, P=.01, η²=0.04). Specifically, participants who received a message emphasizing collective value had a higher intention to share the message than participants who read a message emphasizing individual value (F_3,165=6.87, P=.01, η²=0.04), and the perceived responsibility for message sharing played a mediating role (indirect effect=0.23, 95% lower limit confidence interval [LLCI] 0.41, 95% upper limit confidence interval [ULCI] 0.07). In addition, gain framing facilitated influenza vaccination intention more than loss framing (F_3,166=5.96, P=.02, η²=0.04). However, experiment 2 did not find that message framing affected message-sharing willingness. Neither experiment found an interaction between value type and message framing.

Conclusions

Strengthened individual value rather than collective value is more likely to persuade Chinese adults to vaccinate. However, these adults are more likely to share a message that emphasizes collective rather than individual value, and the perceived responsibility for message sharing plays a mediating role.

Rotavirus and the web: analysis of online conversations in Italy during 2020

Rotavirus is the most common cause of severe diarrhea among children worldwide. In 2017, Italy included rotavirus vaccination in its National Immunization Program. The use of social media monitoring, an efficient tool to understand vaccine hesitancy, has increased in recent years; however, only a few examples of such monitoring are available for Italy. Present study analyzed content on online sources, including social media, to identify factors contributing to Italian parents’ decisions to vaccinate or not their children against rotavirus. Blogmeter Suite was used to search and analyze conversations related to rotavirus in Italian on online sources during 2020. These data were compared with data from 2019. There were 2250 mentions of “rotavirus” recorded; 1080 were related to the rotavirus vaccine. Terms and hashtags used were similar in both years. Facebook was the main source of influence, Instagram dominated the engagement (the sum of interactions related to a post), and Google Trends showed a 5-year upward trend in searches for rotavirus vaccine. Of 1270 sentiment opinions, 60.7% were negative. More parents were familiar with the disease and the vaccine in 2020 compared with 2019. Pediatricians were the most influential healthcare professionals (59.2% of mentions), followed by vaccination staff (33.4%). The most relevant factors for vaccine hesitancy were fear of adverse events, concerns about the vaccination schedule, and COVID-19. Present study represents the first web listening analysis of online discussions about rotavirus. The results can be used to inform targeted communication to counteract misinformation and raise awareness about rotavirus vaccination among parents.

Accuracy of health-related information regarding COVID-19 on Twitter during a global pandemic

This study was performed to analyze the accuracy of health-related information on Twitter during the coronavirus disease 2019 (COVID-19) pandemic. Authors queried Twitter on three dates for information regarding COVID-19 and five terms (cure, emergency or emergency room, prevent or prevention, treat or treatments, vitamins or supplements) assessing the first 25 results with health-related information. Tweets were authoritative if written by governments, hospitals, or physicians. Two physicians assessed each tweet for accuracy. Metrics were compared between accurate and inaccurate tweets using χ ² analysis and Mann-Whitney U. A total of 25.4% of tweets were inaccurate. Accurate tweets were more likely written by Twitter authenticated authors (49.8% vs. 20.9%, 28.9% difference, 95% confidence interval [CI]: 17.7-38.2) with accurate tweet authors having more followers (19,491 vs. 7346; 3446 difference, 95% CI: 234-14,054) versus inaccurate tweet authors. Likes, retweets, tweet length, botometer scores, writing grade level, and rank order did not differ between accurate and inaccurate tweets. We found 1/4 of health-related COVID-19 tweets inaccurate indicating that the public should not rely on COVID-19 health information written on Twitter. Ideally, improved government regulatory authority, public/private industry oversight, independent fact-checking, and artificial intelligence algorithms are needed to ensure inaccurate information on Twitter is removed.

Assessing COVID-19 Vaccine Hesitancy, Confidence, and Public Engagement: A Global Social Listening Study

Background

Monitoring public confidence and hesitancy is crucial for the COVID-19 vaccine rollout. Social media listening (infoveillance) can not only monitor public attitudes on COVID-19 vaccines but also assess the dissemination of and public engagement with these opinions.

Objective

This study aims to assess global hesitancy, confidence, and public engagement toward COVID-19 vaccination.

Methods

We collected posts mentioning the COVID-19 vaccine between June and July 2020 on Twitter from New York (United States), London (United Kingdom), Mumbai (India), and Sao Paulo (Brazil), and Sina Weibo posts from Beijing (China). In total, we manually coded 12,886 posts from the five global metropolises with high COVID-19 burdens, and after assessment, 7032 posts were included in the analysis. We manually double-coded these posts using a coding framework developed according to the World Health Organization’s Confidence, Complacency, and Convenience model of vaccine hesitancy, and conducted engagement analysis to investigate public communication about COVID-19 vaccines on social media.

Results

Among social media users, 36.4% (571/1568) in New York, 51.3% (738/1440) in London, 67.3% (144/214) in Sao Paulo, 69.8% (726/1040) in Mumbai, and 76.8% (2128/2770) in Beijing indicated that they intended to accept a COVID-19 vaccination. With a high perceived risk of getting COVID-19, more tweeters in New York and London expressed a lack of confidence in vaccine safety, distrust in governments and experts, and widespread misinformation or rumors. Tweeters from Mumbai, Sao Paulo, and Beijing worried more about vaccine production and supply, whereas tweeters from New York and London had more concerns about vaccine distribution and inequity. Negative tweets expressing lack of vaccine confidence and misinformation or rumors had more followers and attracted more public engagement online.

Conclusions

COVID-19 vaccine hesitancy is prevalent worldwide, and negative tweets attract higher engagement on social media. It is urgent to develop an effective vaccine campaign that boosts public confidence and addresses hesitancy for COVID-19 vaccine rollouts.

Analyzing Indian general public's perspective on anxiety, stress and trauma during Covid-19 - A machine learning study of 840,000 tweets

BACKGROUND AND AIMS

Ever since COVID-19 was declared a pandemic by WHO in late March 2020, more and more people began to share their opinions online about the anxiety, stress, and trauma they suffered because of the pandemic. However, very few studies were conducted to analyze the general public's perception of what causes stress, anxiety, and trauma during COVID-19. This study focuses particularly on understanding Indian citizens.

METHODS

By using Machine learning techniques, particularly Natural language processing, this study focuses on understanding the attitude of Indian citizens while discussing the anxiety, stress, and trauma created because of COVID-19 and the major reasons that cause it. We used Tweets as data for this study. We have used 840,000 tweets for this study.

RESULTS

Our sentiment analysis study revealed the interesting fact that, even while discussing about the stress, anxiety, and trauma caused by COVID-19, most of the tweets were in neutral sentiments. Death and Lockdown caused by the COVID-19 were the two most important aspects that cause stress, anxiety, and Trauma among Indian citizens.

CONCLUSION

It is important for policymakers and health professionals to understand common citizen's perspectives of what causes them stress, anxiety, and trauma to formulate policies and treat the patients. Our study shows that Indian citizens use social media to share their opinions about COVID-19 and as a coping mechanism in unprecedented time.

Social Media and Health Care, Part I: Literature Review of Social Media Use by Health Care Providers

BACKGROUND

As the world continues to advance technologically, social media (SM) is becoming an essential part of billions of people's lives worldwide and is affecting almost every industry imaginable. As the world is becoming more digitally oriented, the health care industry is increasingly visualizing SM as an important channel for health care promotion, employment, recruiting new patients, marketing for health care providers (HCPs), building a better brand name, etc. HCPs are bound to ethical principles toward their colleagues, patients, and the public in the digital world as much as in the real world.

OBJECTIVE

This review aims to shed light on SM use worldwide and to discuss how it has been used as an essential tool in the health care industry from the perspective of HCPs.

METHODS

A literature review was conducted between March and April 2020 using MEDLINE, PubMed, Google Scholar, and Web of Science for all English-language medical studies that were published since 2007 and discussed SM use in any form for health care. Studies that were not in English, whose full text was not accessible, or that investigated patients' perspectives were excluded from this part, as were reviews pertaining to ethical and legal considerations in SM use.

RESULTS

The initial search yielded 83 studies. More studies were included from article references, and a total of 158 studies were reviewed. SM uses were best categorized as health promotion, career development or practice promotion, recruitment, professional networking or destressing, medical education, telemedicine, scientific research, influencing health behavior, and public health care issues.

CONCLUSIONS

Multidimensional health care, including the pairing of health care with SM and other forms of communication, has been shown to be very successful. Striking the right balance between digital and traditional health care is important.

What social media told us in the time of COVID-19: a scoping review

With the onset of the COVID-19 pandemic, social media has rapidly become a crucial communication tool for information generation, dissemination, and consumption. In this scoping review, we selected and examined peer-reviewed empirical studies relating to COVID-19 and social media during the first outbreak from November, 2019, to November, 2020. From an analysis of 81 studies, we identified five overarching public health themes concerning the role of online social media platforms and COVID-19. These themes focused on: surveying public attitudes, identifying infodemics, assessing mental health, detecting or predicting COVID-19 cases, analysing government responses to the pandemic, and evaluating quality of health information in prevention education videos. Furthermore, our Review emphasises the paucity of studies on the application of machine learning on data from COVID-19-related social media and a scarcity of studies documenting real-time surveillance that was developed with data from social media on COVID-19. For COVID-19, social media can have a crucial role in disseminating health information and tackling infodemics and misinformation.

An analysis of attitude of general public toward COVID-19 crises – sentimental analysis and a topic modeling study

Purpose

It has been eight months into the global pandemic health crises COVID-19, yet the severity of the crises is just getting worse in many parts of the world. At this stage, it is essential to understand and observe the general attitude of the public toward COVID crises and the major concerns the public has voiced out and how it varies across months. Understanding the impact that the COVID-19 crises have created also helps policymakers and health-care organizations access the primary steps that need to be taken for the welfare of the community. The purpose of this study is to understand the general public's response towards COVID-19 crises and the major issues that concerns them.

Design/methodology/approach

For the analysis, data were collected from Twitter. Tweets regarding COVID-19 crises were collected from February 1, 2020, to June 27, 2020. In all, 433,195 tweets were used for this study. Natural language processing (NLP), which is a part of Machine learning, was used for this study. NLP was used to track the changes in the general public's sentiment toward COVID-19 crises and LDA was used to understand the issues that shape the general public's sentiments the crises time. Using Python library Wordcloud, the authors further derived how the primary concerns regarding COVID crises various from February to June of the year 2020.

Findings

This study was conducted in two parts. Study 1 results showed that the attitude of the general public toward COVID crises was reasonably neutral at the beginning of the crises (Month of February). As the crises become severe, the sentiments toward COVID increasingly become negative yet a considerable percentage of neutral sentiments existed even at the peak time of the crises. Study 2 finds out that issues including the severity of the disease, Precautionary measures need to be taken, and Personal issues like unemployment and traveling during the pandemic time were identified as the public's primary concerns.

Originality/value

The research adds value to the literature on understanding the major issues and concerns, the public voices out about the current ongoing pandemic. To the best of the authors’ knowledge, this is the first study with an extended period of timeframe (Five months). In this research, the authors have collected data till June for analysis that makes the results and findings more relevant to the current time.

The Impact of Social Media on the Acceptance of the COVID-19 Vaccine: A Cross-Sectional Study from Saudi Arabia

INTRODUCTION

Social media platforms are used by many people to seek and share health-related information that may influence their decision-making about COVID-19 vaccination.

PURPOSE

The objective of this study is to understand the influence of social media on the attitudes and willingness of the general public of the Aseer region of Saudi Arabia to receive COVID-19 vaccination.

MATERIALS AND METHODS

A cross-sectional self-administrated online survey was conducted in Saudi Arabia Aseer region, where 613 persons willingly took part in the survey in April and May 2021. Residents of Aseer in Saudi Arabia, who are over the age of 18 (eligible for COVID-19 vaccination) and willing to participate in the survey, were included in the study.

RESULTS

Overall, 74.6% agreed that the COVID-19 vaccine was misrepresented via social media. However, 37% of those respondents strongly agreed that social media had increased their willingness to get the COVID-19 vaccine. In addition, employees reported (21.8%) or strongly agreed (28%) that the quantity and quality of information on social media has a detrimental impact on their psychological well-being. Additionally, participants also agreed (21.8%) or strongly agreed (28%) that social media had a negative effect on their psychological condition.

CONCLUSION

The study provides that there was a high degree of awareness indicated among Aseer population regarding misleading information about COVID-19 vaccination via social media. Thus, social media that can share up-to-date scientific information about vaccination must be utilized optimally by the government to assist people in making decisions about accepting vaccinations.

Interventions to support consumer evaluation of online health information credibility: A scoping review

PURPOSE

Various interventions have been designed to help consumers better evaluate the credibility of online health information (OHI). However, assessing information credibility remained the most widely reported challenge by online health consumers. This review aims to provide an overview of major intervention approaches for improving consumer ability to evaluate OHI credibility in order to identify opportunities for future interventions.

METHODS

A scoping review was performed. Seven relevant scientific databases were searched to identify articles that report the design and/or evaluation of interventions to support, facilitate, or assist consumers in assessing the credibility of OHI. Thirty-one articles met the inclusion criteria. Relevant content was extracted from the articles and all codes were validated by second coders.

RESULTS

Three major intervention approaches for enhancing consumers' ability to evaluate OHI credibility were identified: educational program, algorithm, and interactive interface. The design of most interventions (particularly the credibility evaluation component) lacked the guidance of theories, and very few studies systematically evaluated their effectiveness in real online search contexts. Few interventions can provide spontaneous support to consumers while they search online.

CONCLUSION

Our understanding of what theoretical constructs contribute to effective OHI credibility evaluation interventions and how intervention outcomes should be measured remained limited. Future efforts need to focus on the design, development, test, and evaluation of theory-guided OHI credibility evaluation interventions that are scalable, sustainable, and can provide real-time support to consumers.

The sources and correlates of exposure to vaccine-related (mis)information online

Objectives

To assess the quantity and type of vaccine-related information Americans consume online and its relationship to social media use and attitudes toward vaccines.

Methods

Analysis of individual-level web browsing data linked with survey responses from representative samples of Americans collected between October 2016 and February 2019.

Results

We estimate that approximately 84% of Americans visit a vaccine-related webpage each year. Encounters with vaccine-skeptical content are less frequent; they make up only 7.5% of vaccine-related pageviews and are encountered by only 18.5% of people annually. However, these pages are more likely to be published by untrustworthy sources. Moreover, skeptical content exposure is more common among people with less favorable vaccine attitudes. Finally, usage of online intermediaries is frequently linked to vaccine-related information exposure. Google use is differentially associated with subsequent exposure to non-skeptical content, whereas exposure to vaccine-skeptical webpages is associated with usage of webmail and, to a lesser extent, Facebook.

Conclusions

Online exposure to vaccine-skeptical content is relatively rare, but vigilance is required given the potential for exposure among vulnerable audiences.

Analysis of the Anti-Vaccine Movement in Social Networks: A Systematic Review

The aim of this study was to analyze social networks’ information about the anti-vaccine movement. A systematic review was performed in PubMed, Scopus, CINAHL and CUIDEN databases. The search equations were: “vaccine AND social network” and “vaccine AND (Facebook[title] OR Twitter[title] OR Instagram[title] OR YouTube[title])”. The final sample was n = 12, including only articles published in the last 10 years, in English or Spanish. Social networks are used by the anti-vaccine groups to disseminate their information. To do this, these groups use different methods, including bots and trolls that generate anti-vaccination messages and spread quickly. In addition, the arguments that they use focus on possible harmful effects and the distrust of pharmaceuticals, promoting the use of social networks as a resource for finding health-related information. The anti-vaccine groups are able to use social networks and their resources to increase their number and do so through controversial arguments, such as the economic benefit of pharmaceuticals or personal stories of children to move the population without using reliable or evidence-based content.

Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study

Background

The recent coronavirus disease (COVID-19) pandemic is taking a toll on the world’s health care infrastructure as well as the social, economic, and psychological well-being of humanity. Individuals, organizations, and governments are using social media to communicate with each other on a number of issues relating to the COVID-19 pandemic. Not much is known about the topics being shared on social media platforms relating to COVID-19. Analyzing such information can help policy makers and health care organizations assess the needs of their stakeholders and address them appropriately.

Objective

This study aims to identify the main topics posted by Twitter users related to the COVID-19 pandemic.

Methods

Leveraging a set of tools (Twitter’s search application programming interface (API), Tweepy Python library, and PostgreSQL database) and using a set of predefined search terms (“corona,” “2019-nCov,” and “COVID-19”), we extracted the text and metadata (number of likes and retweets, and user profile information including the number of followers) of public English language tweets from February 2, 2020, to March 15, 2020. We analyzed the collected tweets using word frequencies of single (unigrams) and double words (bigrams). We leveraged latent Dirichlet allocation for topic modeling to identify topics discussed in the tweets. We also performed sentiment analysis and extracted the mean number of retweets, likes, and followers for each topic and calculated the interaction rate per topic.

Results

Out of approximately 2.8 million tweets included, 167,073 unique tweets from 160,829 unique users met the inclusion criteria. Our analysis identified 12 topics, which were grouped into four main themes: origin of the virus; its sources; its impact on people, countries, and the economy; and ways of mitigating the risk of infection. The mean sentiment was positive for 10 topics and negative for 2 topics (deaths caused by COVID-19 and increased racism). The mean for tweet topics of account followers ranged from 2722 (increased racism) to 13,413 (economic losses). The highest mean of likes for the tweets was 15.4 (economic loss), while the lowest was 3.94 (travel bans and warnings).

Conclusions

Public health crisis response activities on the ground and online are becoming increasingly simultaneous and intertwined. Social media provides an opportunity to directly communicate health information to the public. Health systems should work on building national and international disease detection and surveillance systems through monitoring social media. There is also a need for a more proactive and agile public health presence on social media to combat the spread of fake news.

Recommending research articles to consumers of online vaccination information

Online health communications often provide biased interpretations of evidence and have unreliable links to the source research. We tested the feasibility of a tool for matching web pages to their source evidence. From 207,538 eligible vaccination-related PubMed articles, we evaluated several approaches using 3,573 unique links to web pages from Altmetric. We evaluated methods for ranking the source articles for vaccine-related research described on web pages, comparing simple baseline feature representation and dimensionality reduction approaches to those augmented with canonical correlation analysis (CCA). Performance measures included the median rank of the correct source article; the percentage of web pages for which the source article was correctly ranked first (recall@1); and the percentage ranked within the top 50 candidate articles (recall@50). While augmenting baseline methods using CCA generally improved results, no CCA-based approach outperformed a baseline method, which ranked the correct source article first for over one quarter of web pages and in the top 50 for more than half. Tools to help people identify evidence-based sources for the content they access on vaccination-related web pages are potentially feasible and may support the prevention of bias and misrepresentation of research in news and social media.