COVID-19 and the "Film Your Hospital" Conspiracy Theory: Social Network Analysis of Twitter Data

The Influence of Joe Wicks on Physical Activity During the COVID-19 Pandemic: Thematic, Location, and Social Network Analysis of X Data

BACKGROUND

 Social media (SM) was essential in promoting physical activity during the COVID-19 pandemic, especially among people confined to their homes. Joe Wicks, a fitness coach, became particularly popular on SM during this time, posting daily workouts that millions of people worldwide followed.

OBJECTIVE

 This study aims to investigate the influence of Joe Wicks on SM and the impact of his content on physical activity levels among the public.

METHODS

 We used NodeXL Pro (Social Media Research Foundation) to collect data from X (formerly Twitter) over 54 days (March 23, 2020, to May 15, 2020), corresponding to the strictest lockdowns in the United Kingdom. We collected 290,649 posts, which we analyzed using social network analysis, thematic analysis, time-series analysis, and location analysis.

RESULTS

 We found that there was significant engagement with content generated by Wicks, including reposts, likes, and comments. The most common types of posts were those that contained images, videos, and text of young people (school-aged children) undertaking physical activity by watching content created by Joe Wicks and posts from schools encouraging pupils to engage with the content. Other shared posts included those that encouraged others to join the fitness classes run by Wicks and those that contained general commentary. We also found that Wicks' network of influence was extensive and complex. It contained numerous subcommunities and resembled a broadcast network shape. Other influencers added to engagement with Wicks via their networks. Our results show that influencers can create networks of influence that are exhibited in distinctive ways.

CONCLUSIONS

Our study found that Joe Wicks was a highly influential figure on SM during the COVID-19 pandemic and that his content positively impacted physical activity levels among the public. Our findings suggest that influencers can play an important role in promoting public health and that government officials should consider working with influencers to communicate health messages and promote healthy behaviors. Our study has broader implications beyond the status of fitness influencers. Recognizing the critical role of individuals such as Joe Wicks in terms of health capital should be a critical area of inquiry for governments, public health authorities, and policy makers and mirrors the growing interest in health capital as part of embodied and digital experiences in everyday life.

Characterizing the Gendered Twitter Discussion of COVID-19 Hoax

We collected data from Twitter and used content analysis to better understand the gendered discussion around COVID-19 as a hoax. We identified three main categories in the inductive stage of the research: (1) sympathetic to human rights & perceived injustice, (2) invincibility and superiority of COVID hoaxers, (3) conspiracies and/or hidden agendas. The findings of the study show that among all gender groups, the first category is the most dominant (44.4%), the third category is the second most frequent (35.6%), and the last category (19.9%) is the least frequent. However, when the discussion is centered on men (40.2%) and gender and sexual minorities (GSM; 69.6%) groups, the last category is the most dominant with regard to stigmatizing GSM groups by falsely associating them with progressive secret agendas. As for women's group, being sympathetic to human rights and the perceived injustice against them during the pandemic constitute the most dominant category (51.5%). We discuss the implications of the study in the conclusion.

A cross-lingual analysis on the spread of misinformation using the case of Ivermectin as a treatment for Covid-19

The spread of misinformation transgresses international boundaries, between languages and cultures. This is especially evident in times of global crises such as the Covid-19 pandemic. This study observes misinformation on Twitter in the Japanese and English languages regarding false claims that the drug Ivermectin is an effective treatment for Covid-19. Our exploratory cross-lingual analysis identifies key themes of discussion and influential users in both languages, finding English misinformation to be highly popular amongst Japanese users. Significantly, an analysis of the timing of retweets between languages reveals that Japanese users find and widely share English misinformation often before English users themselves. This contradicts expectations that users from other languages tend to pick up on popular misinformation in English. Instead, they seek out English language sources irrespective of their popularity to support their agenda. These results emphasise the importance of cross-lingual mitigation strategies for organizations trying to combat misinformation, and that they must look beyond their own language spheres.

Information Circulation Among Spanish-Speaking and Caribbean Communities Related to COVID-19: Social Media-Based Multidimensional Analysis

BACKGROUND

Scientific studies from North America and Europe tend to predominate the internet and benefit English-speaking users. Meanwhile, the COVID-19 death rate was high at the onset of the pandemic in Spanish-speaking countries, and information about nearby Caribbean countries was rarely highlighted. Given the rise in social media use in these regions, the web-based dissemination of scientific information related to COVID-19 must be thoroughly examined.

OBJECTIVE

This study aimed to provide a multidimensional analysis of peer-reviewed information circulation related to COVID-19 in Spanish-speaking and Caribbean regions.

METHODS

COVID-19-related, peer-reviewed resources shared by web-based accounts located in Spanish-speaking and Caribbean regions were identified through the Altmetric website, and their information was collected. A multidimensional model was used to examine these resources, considering time, individuality, place, activity, and relations. Time was operationalized as the 6 dates of data collection, individuality as the knowledge area and accessibility level, place as the publication venue and affiliation countries, activity as the Altmetric score and number of mentions in the selected regions, and relations as coauthorship between countries and types of social media users who disseminated COVID-19-related information.

RESULTS

The highest information circulation peaks in Spanish-speaking countries were from April 2020 to August 2020 and from December 2020 to April 2021, whereas the highest peaks in Caribbean regions were from December 2019 to April 2020. Regarding Spanish-speaking regions, at the onset of the pandemic, scientific expertise was concentrated on a few peer-reviewed sources written in English. The top scientific journals mentioned were from English-speaking, westernized regions, whereas the top scientific authorships were from China. The most mentioned scientific resources were about breakthrough findings in the medical and health sciences area, written in highly technical language. The top relationships were self-loops in China, whereas international collaborations were between China and the United States. Argentina had high closeness and betweenness, and Spain had high closeness. On the basis of social media data, a combination of media outlets; educational institutions; and expert associations, particularly from Panama, influenced the diffusion of peer-reviewed information.

CONCLUSIONS

We determined the diffusion patterns of peer-reviewed resources in Spanish-speaking countries and Caribbean territories. This study aimed to advance the management and analysis of web-based public data from non-white people to improve public health communication in their regions.

Analysing Twitter's Role in Combating the Magnetic Vaccine Conspiracy Theory Using Social Network Analysis

BACKGROUND

The popularity of the magnetic vaccine conspiracy theory, and others of a similar nature, creates challenges to promoting vaccines and disseminating accurate health information.

OBJECTIVE

Health conspiracy theories are gaining in popularity. The study's objective was to evaluate the Twitter social media network related to the magnetic vaccination conspiracy theory and to apply social capital theory to analyse the unique social structures of influential users. As a strategy for online public health surveillance, we employ social network analysis to identify the important opinion leaders sharing the conspiracy, the key websites, and the narratives.

METHODS

A total of 18,706 tweets were retrieved and analysed using social network analysis. Data were retrieved from June 01 to June 13 (2021) using the keyword 'vaccine magnetic'. Tweets were retrieved via a dedicated Twitter Application Programming Interface (API). More specifically, the Academic Track API was used, and the data were analysed using NodeXL Pro and Gephi.

RESULTS

There were a total of 22,762 connections between Twitter users within the dataset. The study found that the most influential user within the network consisted of a news account that was reporting on the conspiracy. There were also several other users that became influential such as an epidemiologist, a health economist, and a retired sports athlete who exerted their social capital within the network.

CONCLUSIONS

Our study finds that influential users were effective broadcasters against the conspiracy, and their reach extended beyond their own network of Twitter followers. We emphasise the need for trust in contact with influential users concerning health information, particularly in the context of widespread social uncertainty resulting from the pandemic, when public sentiment on social media may be unpredictable. The study highlights the potential of influential users to disrupt information flows of conspiracy theories due to their unique social capital.

CLINICALTRIAL

Health Literacy and Critical Lecture as Key Elements to Detect and Reply to Nutrition Misinformation on Social Media: Analysis between Spanish Healthcare Professionals

Health misinformation about nutrition and other health aspects on social media is a current public health concern. Healthcare professionals play an essential role in efforts to detect and correct it. The present study focuses on analyzing the use of competencies associated with training in methodology, health literacy, and critical lecture in order to detect sources of health misinformation that use scientific articles to support their false information. A qualitative study was conducted between 15 and 30 January 2022, wherein the participants were recruited from active users from a nutrition conversation on Twitter, diets, and cancer and defined themselves as healthcare professionals. This study demonstrates that health literacy and critical lecture competencies allow for the detection of more misinformation messages and are associated with a high rate of responses to users that spread the misinformation messages. Finally, this study proposes the necessity of developing actions to improve health literacy and critical lecture competencies between healthcare professionals. However, in order to achieve this, health authorities must develop strategies to psychologically support those healthcare professionals faced with bullying as a result of their activity on social media debunking health hoaxes.

Public Opinion Manipulation on Social Media: Social Network Analysis of Twitter Bots during the COVID-19 Pandemic

Social media is not only an essential platform for the dissemination of public health-related information, but also an important channel for people to communicate during the COVID-19 pandemic. However, social bots can interfere with the social media topics that humans follow. We analyzed and visualized Twitter data during the prevalence of the Wuhan lab leak theory and discovered that 29% of the accounts participating in the discussion were social bots. We found evidence that social bots play an essential mediating role in communication networks. Although human accounts have a more direct influence on the information diffusion network, social bots have a more indirect influence. Unverified social bot accounts retweet more, and through multiple levels of diffusion, humans are vulnerable to messages manipulated by bots, driving the spread of unverified messages across social media. These findings show that limiting the use of social bots might be an effective method to minimize the spread of conspiracy theories and hate speech online.

When the influencer says jump! How influencer signaling affects engagement with COVID-19 misinformation

With signaling theory, credibility, and social media engagement (SME) as guiding frameworks, this study used an experiment to examine how social media influencers (SMIs) affect how people engage with COVID-19 misinformation. SMI-promoted information elicited more SME, credibility, and purchase likelihood than non-SMI promoted information. The most effective message was a post promoted by an SMI that contained detailed information about an authentic product. However, data indicated nuance regarding the effect of SMIs. The authenticity of the information as well as the amount of detail in the post played a role. Additionally, mediated effects analysis showed that the impact of SME on purchase likelihood was higher among non-SMI followers. Data suggests that using a multi-signal messaging approach is suitable regardless of promotion by an SMI. This has important implications to public health messaging and the author discusses how health agencies may effectively signal information to the public.

Ecosystem Services: A Social and Semantic Network Analysis of Public Opinion on Twitter

Social media data reveal patterns of knowledge, attitudes, and behaviours of users on a range of topics. This study analysed 4398 tweets gathered between 17 January 2022 and 3 February 2022 related to ecosystem services, using the keyword and hashtag "ecosystem services". The Microsoft Excel plugin, NodeXL was used for social and semantic network analysis. The results reveal a loosely dense network in which information is conveyed slowly, with homogeneous, medium-sized subgroups typical of the community cluster structure. Citizens, NGOs, and governmental administrations emerged as the main gatekeepers of information in the network. Various semantic themes emerged such as the protection of natural capital for the sustainable production of ecosystem services; nature-based solutions to protect human structures and wellbeing against natural hazards; socio-ecological systems as the interaction between human beings and the environment; focus on specific services such as the storage of atmospheric CO₂ and the provision of food. In conclusion, the perception of social users of the role of ecosystem services can help policymakers and forest managers to outline and implement efficient forest management strategies and plans.

The #VaccinesWork Hashtag on Twitter in the Context of the COVID-19 Pandemic: Network Analysis

Background

Vaccination is one of the most successful public health interventions for the prevention of COVID-19. Toward the end of April 2021, UNICEF (United Nations International Children’s Emergency Fund), alongside other organizations, were promoting the hashtag #VaccinesWork.

Objective

The aim of this paper is to analyze the #VaccinesWork hashtag on Twitter in the context of the COVID-19 pandemic, analyzing the main messages shared and the organizations involved.

Methods

The data set used in this study consists of 11,085 tweets containing the #VaccinesWork hashtag from the 29th to the 30th of April 2021. The data set includes tweets that may not have the hashtag but were replies or mentions in those tweets. The data were retrieved using NodeXL, and the network graph was laid out using the Harel-Koren fast multiscale layout algorithm.

Results

The study found that organizations such as the World Health Organization, UNICEF, and Gavi were the key opinion leaders and had a big influence on the spread of information among users. Furthermore, the most shared URLs belonged to academic journals with a high impact factor. Provaccination users had other vaccination-promoting hashtags in common, not only in the COVID-19 scenario.

Conclusions

This study investigated the discussions surrounding the #VaccinesWork hashtag. Social media networks containing conspiracy theories tend to contain dubious accounts leading the discussions and are often linked to unverified information. This kind of analysis can be useful to detect the optimal moment for launching health campaigns on Twitter.

COVID-19 Conspiracy Theories Discussion on Twitter

The coronavirus disease 2019 (COVID-19) pandemic was an unexpected event and resulted in catastrophic consequences with long-lasting behavioral effects. People began to seek explanations for different aspects of COVID-19 and resorted to conspiracy narratives. The objective of this article is to analyze the changes on the discussion of different COVID-19 conspiracy theories throughout the pandemic on Twitter. We have collected a data set of 1.269 million tweets associated with the discussion on conspiracy theories between January 2020 and November 2021. The data set includes tweets related to eight conspiracy theories: the 5G, Big Pharma, Bill Gates, biological weapon, exaggeration, FilmYourHospital, genetically modified organism (GMO), and the vaccines conspiracy. The analysis highlights several behaviors in the discussion of conspiracy theories and allows categorizing them into four groups. The first group are conspiracy theories that peaked at the beginning of the pandemic and sharply declined afterwards, including the 5G and FilmYourHospital conspiracies. The second group associated with the Big Pharma and vaccination-related conspiracy whose role increased as the pandemic progressed. The third are conspiracies that remained persistent throughout the pandemic such as exaggeration and Bill Gates conspiracies. The fourth are those that had multiple peaks at different times of the pandemic including the GMO and biological weapon conspiracies. In addition, the number of COVID-19 new cases was found to be a significant predictor for the next week tweet frequency for most of the conspiracies.

Théories du complot et COVID-19 : comment naissent les croyances complotistes ?

La pandémie COVID-19 causée par le nouveau coronavirus SARS-CoV-2 a provoqué une crise mondiale sans précédent, associée à une prolifération de théories du complot. La prévalence de ces croyances complotistes a participé à affaiblir la crédibilité des mesures gouvernementales de santé publique, limiter l'accès des citoyens aux sources d’information fiables, et perturber la réponse des systèmes de santé face à la crise sanitaire. Plusieurs hypothèses ont été proposées en psychologie et en sciences sociales pour comprendre la genèse de ces croyances dans des contextes épidémiques, associant l’implication conjointe de facteurs psychologiques (comme la volonté de préserver sa sécurité, de maintenir une image de soi positive, ou encore de renforcer son rôle social) et sociodémographiques (comme les caractéristiques générationnelles, socioculturelles et politiques des individus). Toutefois, les découvertes récentes en sciences cognitives à propos des mécanismes élémentaires de traitement de l'information offrent un nouvel éclairage sur la génération des croyances conspirationnistes à travers les époques et les cultures. Dans cet article, nous proposons une définition de la théorie du complot et une classification des croyances complotistes pendant la pandémie de COVID-19. Nous montrons comment les mécanismes de génération et de mise à jour des croyances permettent d'expliquer la genèse des théories du complot, et nous proposons plusieurs hypothèses étayées par les recherches contemporaines en sciences cognitives et en sciences sociales à propos des théories du complot.

Understanding Melanoma Talk on Twitter: The Lessons Learned and Missed Opportunities

BACKGROUND

Melanoma is the third most common cause of cancer and the deadliest form of skin cancer among 17-39 year-olds in the United States. Melanoma is a critical public health issue with a substantial economic burden. Cases and associated burdens, however, could be prevented with a greater awareness of, and interventions related to, skin cancer and melanoma-related preventive behaviors. In fact, as social media use is close to ubiquitous, it represents a potential communication modality. However, more research is needed to understand the current state of melanoma-related information exchanged between Twitter users. This study aimed to understand the different types of users controlling the melanoma-related information diffusion and conversation themes on Twitter.

METHODS

Tweets (n = 692) were imported from Twitter between 1 and 31 May 2021 using the Twitter public API; and uploaded to NodeXL to conduct a social network analysis.

RESULTS

Health professionals and organizations with medical backgrounds were the main content producers, disseminators, and top influencers. However, information diffusion is slow and uneven among users. Additionally, conversations lacked a focus on preventive behaviors.

CONCLUSION

Twitter is a potential platform for the targeted outreach of individuals in melanoma awareness campaigns. This study provides insights maximizing the effectiveness of Twitter as a communication modality. Our findings can help guide the development of customized content and interventions during melanoma awareness campaigns.

Network analysis of the relationships between conspiracy beliefs towards COVID-19 vaccine and symptoms of fear of COVID-19 in a sample of latin american countries

The present study examined how conspiracy beliefs about COVID-19 vaccines specifically relate to symptoms of fear of COVID-19 in a sample of four South American countries. A total of 1785 people from Bolivia, Colombia, Ecuador, and Peru participated, responding to a sociodemographic survey, the Fear of COVID-19 scale (FCV-19 S) and the Vaccine Conspiracy Beliefs Scale-COVID-19 (VCBS-COVID-19). Network analysis identified the most important symptoms of fear and conspiracy beliefs about COVID-19 vaccines (nodes) and the associations between them (edges). In addition, the robustness of the network of these indicators of centrality and the possible differences in the structure and connectivity of the networks between the four countries were evaluated. The results suggest that the nodes with the highest centrality were items 2 and 5 of the FCV-19 S and item 2 of the VCBS-COVID-19. Likewise, item 6 is the belief that most predicts conspiracy beliefs about vaccines against COVID-19; while item 6 was the symptom that most predicts fear of COVID-19. The findings strongly support cross-cultural similarities in the networks across the four countries rather than differences. Although it was expected that a higher presence of symptoms of fear of COVID-19 may lead people to compensate for their fear by believing in conspiratorial ideas about vaccines and, consequently, rejecting the COVID-19 vaccine, the results do not clearly show this relationship. This could lead other researchers to generate evidence to explain the differences between Latin American countries and countries in other contexts in terms of vaccination rates. This evidence could be useful to develop policies favoring vaccination against COVID-19 that are more contextualized to the Latin American region, characterized by social instability and economic recession during the pandemic.

The Relationship Between Information Sources, Health Literacy, and COVID-19 Knowledge in the COVID-19 Infodemic: Cross-sectional Online Study in Japan

Background

The COVID-19 pandemic has caused not only a disease epidemic but also an infodemic. Due to the increased use of the internet and social media, along with the development of communication technology, information has spread faster and farther during the COVID-19 infodemic. Moreover, the increased choice of information sources has made it more difficult to make sound decisions regarding information. Although social media is the most common source of misinformation, other forms of media can also spread misinformation. However, the media sources used by people with high health literacy and COVID-19 knowledge to obtain information are unclear. Furthermore, the association between the use of multiple information sources and health literacy or COVID-19 knowledge is ill-defined.

Objective

This study aims to examine the following 3 aspects regarding the COVID-19 infodemic: (1) the relationship between health literacy, COVID-19 knowledge, and the number of information sources used; (2) the impact of media use on health literacy; and (3) the impact of media use on COVID-19 knowledge.

Methods

An online cross-sectional study was conducted in November 2021. Participants were 477 individuals aged 20-69 years. After obtaining consent to participate in the study, participants were asked about sociodemographic indicators, sources of health-related information, health literacy, and COVID-19 knowledge. Sources of health-related information were categorized into 4 types: mass media, digital media, social media, and face-to-face communication. The Spearman rank correlation test was conducted to determine the relationship between health literacy, the number of correct answers to COVID-19 knowledge, and the number of information sources used. Multiple regression analysis was conducted with health literacy and the number of correct answers as dependent variables, the 4 media types as independent variables, and age and sex as adjustment variables.

Results

Mass media was the most frequently used source of information, followed by digital media, face-to-face communication, and social media. Social media use was significantly higher among individuals aged 20-29 years than among other age groups. Significant positive correlations were found between health literacy, the number of positive responses to COVID-19 knowledge, and the number of information sources used. Multiple linear regression analysis showed that health literacy is associated with access to information from digital media and face-to-face communication. Additionally, COVID-19 knowledge was associated with access to information from mass media, digital media, and face-to-face communication.

Conclusions

Health literacy and COVID-19 knowledge could be improved using diverse information sources, especially by providing opportunities to use digital media and face-to-face communication. Furthermore, it may be important to improve health literacy and provide accurate knowledge about COVID-19 to young adults.

Public Perceptions around mHealth Applications during COVID-19 Pandemic: A Network and Sentiment Analysis of Tweets in Saudi Arabia

A series of mitigation efforts were implemented in response to the COVID-19 pandemic in Saudi Arabia, including the development of mobile health applications (mHealth apps) for the public. Assessing the acceptability of mHealth apps among the public is crucial. This study aimed to use Twitter to understand public perceptions around the use of six Saudi mHealth apps used during COVID-19: “Sehha”, “Mawid”, “Sehhaty”, “Tetamman”, “Tawakkalna”, and “Tabaud”. We used two methodological approaches: network and sentiment analysis. We retrieved Twitter data using specific mHealth apps-related keywords. After including relevant tweets, our final mHealth app networks consisted of a total of 4995 Twitter users and 8666 conversational relationships. The largest networks in size (i.e., the number of users) and volume (i.e., the conversational relationships) among all were “Tawakkalna” followed by “Tabaud”, and their conversations were led by diverse governmental accounts. In contrast, the four remaining mHealth networks were mainly led by the health sector and media. Our sentiment analysis approach included five classes and showed that most conversations were neutral, which included facts or information pieces and general inquires. For the automated sentiment classifier, we used Support Vector Machine with AraVec embeddings as it outperformed the other tested classifiers. The sentiment classifier showed an accuracy, precision, recall, and F1-score of 85%. Future studies can use social media and real-time analytics to improve mHealth apps’ services and user experience, especially during health crises.

Conspiracy Theories about Infectious Diseases: An Introduction

Understanding why people believe conspiracy theories related to disease outbreaks and the consequences of such beliefs is critical for combating both the COVID-19 pandemic and its corresponding “infodemic.” In the introduction to this special issue on conspiracy theories about infectious diseases, the authors first provide a brief overview of the narratives of conspiracy theories related to COVID-19, followed by a review of extant theoretical frameworks regarding the psychology of conspiracy beliefs. Specifically, they discuss how epistemic, existential, and social needs contribute to the holding of conspiracy beliefs. Then, the authors summarize the major findings from the nine empirical articles featured in this issue, particularly how they shed light on the antecedents and consequences of disease-related conspiracy beliefs. They conclude by discussing future directions for the study of disease-related conspiracy beliefs.

Social network analysis of Twitter data from Pakistan during COVID-19

Purpose

The use of social media has increased during the COVID-19 pandemic. Social media platforms provide opportunities to share news, ideas and personal stories. Twitter is used by citizens in Pakistan to respond and comment on emerging news stories and events. However, it is not known whether Twitter played a positive or negative role in spreading updates and preventive messages during the COVID-19 pandemic. The purpose of this study is to analyse content from Twitter during the pandemic.

Design/methodology/approach

NodeXL was used to retrieve data using the keyword وائرس کورونا (written in Urdu and which translates to Coronavirus). The first data set (Case Study 1) was based on 10,284 Twitter users from the end of March. The second data set (Case Study 2) was based on 10,644 Twitter users from the start of April. The theoretical lens of effective message framing was used to classify the most retweeted content on Twitter.

Findings

Twitter was used for personal and professional projections and included certain tweets included political motives even during the unfolding health crisis. There appeared to be very few successful attempts to use Twitter as a tool for health awareness and risk communication. The empirical findings indicate that the most retweeted messages were gain-framed and can be classified as personal, informative and political in nature.

Originality/value

The present study provides insights likely to be of interest to researchers, health organizations, citizens, government and politicians that are interested in making more effective use of social media for the purposes of health promotion. The authors also provide novel insights into the key topics of discussions, websites and hashtags used by Pakistani Twitter users during the COVID-19 pandemic.

Identification of cohesive subgroups in a university hall of residence during the COVID-19 pandemic using a social network analysis approach

THE AIMS

(i) analyze connectivity between subgroups of university students, (ii) assess which bridges of relational contacts are essential for connecting or disconnecting subgroups and (iii) to explore the similarities between the attributes of the subgroup nodes in relation to the pandemic context. During the COVID-19 pandemic, young university students have experienced significant changes in their relationships, especially in the halls of residence. Previous research has shown the importance of relationship structure in contagion processes. However, there is a lack of studies in the university setting, where students live closely together. The case study methodology was applied to carry out a descriptive study. The participation consisted of 43 university students living in the same hall of residence. Social network analysis has been applied for data analysis. Factions and Girvan-Newman algorithms have been applied to detect the existing cohesive subgroups. The UCINET tool was used for the calculation of the SNA measure. A visualization of the global network will be carried out using Gephi software. After applying the Girvan-Newman and Factions, in both cases it was found that the best division into subgroups was the one that divided the network into 4 subgroups. There is high degree of cohesion within the subgroups and a low cohesion between them. The relationship between subgroup membership and gender was significant. The degree of COVID-19 infection is related to the degree of clustering between the students. College students form subgroups in their residence. Social network analysis facilitates an understanding of structural behavior during the pandemic. The study provides evidence on the importance of gender, race and the building where they live in creating network structures that favor, or not, contagion during a pandemic.

Rethinking Fake News: Disinformation and Ideology during the time of COVID-19 Global Pandemic

Digital media and citizen journalism has escalated the infiltration of fake news attempting to create a post truth society (Lazer et al., 2018). The COVID-19 pandemic has seen a surge of misinformation leading to anti-mask, anti-vaccine and anti-5G protests on a global scale. Although the term ‘misinformation’ has been generalized in media and scholarly work, there is a fundamental difference between how misinformation impacts society, compared to more strategically planned disinformation attacks. In this study we explore the ideological constructs of citizens towards acceptance or rejection of disinformation during the heightened time of a COVID-19 global health crisis. Our analysis follows two specific disinformation propagandas evaluated through social network analysis of Twitter data in addition to qualitative insights generated from tweets and in-depth interviews.

Validation of the COVID-19 Transmission Misinformation Scale and Conditional Indirect Negative Effects on Wearing a Mask in Public

The SARS-CoV-2 (COVID-19) pandemic devastated the world economy. Global infections and deaths altered the behaviors of generations. The Internet acted as an incredible vehicle for communication but was also a source of unfounded rumors. Unfortunately, this freedom of information sharing and fear of COVID-19 fostered unfounded claims about transmission (e.g., 5G networks spread the disease). With negligible enforcement to stop the spread of rumors and government officials spouting unfounded claims, falsities became ubiquitous. Organizations, public health officials, researchers, and businesses spent limited resources addressing rumors instead of implementing policies to overcome challenges (e.g., speaking to defiant mask wearers versus safe reopening actions). The researchers defined COVID-19 transmission misinformation as false beliefs about the spread and prevention of contracting the disease. Design and validation of the 12-item COVID-19 Transmission Misinformation Scale (CTMS) provides a measure to identify transmission misinformation believers. Indirect COVID-19 transmission misinformation beliefs with a fear of COVID-19 decreased wearing a mask in public intentions. Callousness exacerbated COVID-19 transmission misinformation beliefs as a moderator.

The Impact of the Online COVID-19 Infodemic on French Red Cross Actors' Field Engagement and Protective Behaviors: Mixed Methods Study

Background

The COVID-19 pandemic has been widely described as an infodemic, an excess of rapidly circulating information in social and traditional media in which some information may be erroneous, contradictory, or inaccurate. One key theme cutting across many infodemic analyses is that it stymies users’ capacities to identify appropriate information and guidelines, encourages them to take inappropriate or even harmful actions, and should be managed through multiple transdisciplinary approaches. Yet, investigations demonstrating how the COVID-19 information ecosystem influences complex public decision making and behavior offline are relatively few.

Objective

The aim of this study was to investigate whether information reported through the social media channel Twitter, linked articles and websites, and selected traditional media affected the risk perception, engagement in field activities, and protective behaviors of French Red Cross (FRC) volunteers and health workers in the Paris region of France from June to October 2020.

Methods

We used a hybrid approach that blended online and offline data. We tracked daily Twitter discussions and selected traditional media in France for 7 months, qualitatively evaluating COVID-19 claims and debates about nonpharmaceutical protective measures. We conducted 24 semistructured interviews with FRC workers and volunteers.

Results

Social and traditional media debates about viral risks and nonpharmaceutical interventions fanned anxieties among FRC volunteers and workers. Decisions to continue conducting FRC field activities and daily protective practices were also influenced by other factors unrelated to the infodemic: familial and social obligations, gender expectations, financial pressures, FRC rules and communications, state regulations, and relationships with coworkers. Some respondents developed strategies for “tuning out” social and traditional media.

Conclusions

This study suggests that during the COVID-19 pandemic, the information ecosystem may be just one among multiple influences on one group’s offline perceptions and behavior. Measures to address users who have disengaged from online sources of health information and who rely on social relationships to obtain information are needed. Tuning out can potentially lead to less informed decision making, leading to worse health outcomes.

Irrational Beliefs about COVID-19: A Scoping Review

Since the emergence of the recent Coronavirus Disease of 2019 (COVID-19) and its spread as a pandemic, there has been a parallel spread of false and misleading information, known as an infodemic. The COVID-19 infodemic has induced distrust in scientific communities, governments, institutions and the population, and a confidence crisis that has led to harmful health behaviours, also impacting on mental health. The aim of this study is to provide a scoping review of the scientific literature about COVID-19-related misinformation and conspiracy theories, focusing on the construction of a conceptual framework which is useful for the interpretation of the conspiracy theory phenomenon surrounding COVID-19, and its consequences. Particular socio-environmental conditions (i.e., low educational level, younger age), psychological processes and attitudes (such as low levels of epistemic trust, the avoidance of uncertainty, extraversion, collective narcissism, and a conspiracy-prone mindset), and contextual factors (e.g., high levels of self-perceived risk and anxiety) seem to underpin the adherence to beliefs that are not solely the domain of paranoids and extremists but a widespread phenomenon that has caused important health, social and political consequences.

Validation of the COVID-19 Disbelief Scale: Conditional indirect effects of religiosity and COVID-19 fear on intent to vaccinate

The COVID-19 pandemic uprooted economies, infected millions, and altered behaviors. Yet, the invisible nature of the disease, paralleled symptoms to the common flu, and misinformation generated COVID-19 disbelief. Many believed COVID-19 was a hoax. Many believed case numbers were fabricated. Others claimed it was a ruse for sociopolitical reasons. The construction of the 8-item COVID-19 Disbelief Scale (CDS) measures the false belief COVID-19 was not real and life-threatening. The CDS demonstrated discriminant validity and robust reliability across two studies. Predictive analysis evinced COVID-19 disbelievers feared COVID-19 less and had lower intent to get vaccinated. In the U.S., certain religious organizations spread misinformation. Religiosity associated with greater COVID-19 disbelief. Among disbelievers, conditional indirect effects of religiosity associated with greater COVID-19 fear and higher intent to get vaccinated. The moderated mediation model validated utility of the CDS as a concise instrument to study variable relationships.

The COVID-19 pandemic and the search for structure: Social media and conspiracy theories

The study outlines a model for how the COVID-19 pandemic has uniquely exacerbated the propagation of conspiracy beliefs and subsequent harmful behaviors. The pandemic has led to widespread disruption of cognitive and social structures. As people face these disruptions they turn online seeking alternative cognitive and social structures. Once there, social media radicalizes beliefs, increasing contagion (rapid spread) and stickiness (resistance to change) of conspiracy theories. As conspiracy theories are reinforced in online communities, social norms develop, translating conspiracy beliefs into real-world action. These real-world exchanges are then posted back on social media, where they are further reinforced and amplified, and the cycle continues. In the broader population, this process draws attention to conspiracy theories and those who confidently espouse them. This attention can drive perceptions that conspiracy beliefs are less fringe and more popular, potentially normalizing such beliefs for the mainstream. We conclude by considering interventions and future research to address this seemingly intractable problem.

Social Media Conversations About High Engagement Sports Team Brands

This study conducts an analysis of social media discussions related to high engagement sports brands. More specifically, our study examined the English Premier League (EPL); it sought to retrieve data systematically over the same day, weekly, for a period of five months. After this process, we had built 20 datasets and NodeXL was utilized to analyse the data. After we had this data, we were able to use qualitative observations to identify key users and conversations that formed around the EPL as well as the connections between the conversations that arose from the brand’s posts and the people involved in them. We also analyzed the quantitative data underpinning our network visualisations to provide further insights. The most obvious initial finding was that when the EPL tweets, it prompts a large volume of conversations directly related to these tweets. However, we also noted that EPL tweets also help instigate further, sometimes unrelated, tweets and conversations. More specifically, we identified that the visualized network of conversations was of a broadcast form, which is characterized by messages being generated by a central account (the EPL) and shared by a number of decentralized users. Based on our analysis, we propose guidance around (S)ocial media presence, (C)rafting the message, Planned (i)ntervention, (S)pontaneous follow-up, and (M)essage mortality to form the SCISM framework. This framework is likely to be of interest to brands that wish to promote, sustain and benefit from their instigation of social media.

Plandemic Revisited: A Product of Planned Disinformation Amplifying the COVID-19 "infodemic"

During the first few months of the COVID-19 pandemic, a 26-min documentary entitled Plandemic was released online and fanatically shared via Twitter and other major social media platforms. The producers of the documentary sought to spread misinformation and conspiracy theories and to discredit scientific experts using a sophisticated disinformation campaign. They set out to accomplish this by coaching citizens toward activism to maximize the speed at which the documentary propagated and decrease positive sentiments toward public health interventions. Applying techniques from social network analysis in conjunction with a formative content analysis of Twitter data, we examined the effectiveness of the Plandemic disinformation campaign as a case study of social engineering during the COVID-19 pandemic. By comparing the Twitter network's community structure and communication patterns before and after the release of the film, we demonstrate the Plandemic campaign to have been effective for two reasons. First, the campaign established a decentralized information sharing network on Twitter by coaching low-reach social media users to mass share the documentary, effectively subverting efforts to gatekeep its misinformation. Second, the campaign amplified negative sentiments regarding vaccination and containment measures among conspiracy theorists. These effects possibly have an indirect impact on the public's willingness to comply with public health measures. Our results show the necessity of further research about sophisticated social experiments such as the Plandemic disinformation campaign and provide important insights for policy-making to combat the spread of health misinformation during public health crises.

Antivaccine Movement and COVID-19 Negationism: A Content Analysis of Spanish-Written Messages on Twitter

During the COVID-19 pandemic, different conspiracies have risen, with the most dangerous being those focusing on vaccines. Today, there exists a social media movement focused on destroying the credibility of vaccines and trying to convince people to ignore the advice of governments and health organizations on vaccination. Our aim was to analyze a COVID-19 antivaccination message campaign on Twitter that uses Spanish as the main language, to find the key elements in their communication strategy. Twitter data were retrieved from 14 to 28 December using NodeXL software. We analyzed tweets in Spanish, focusing on influential users, most influential tweets, and content analysis of tweets. The results revealed ordinary citizens who 'offer the truth' as the most important profile in this network. The content analysis showed antivaccine tweets (31.05%) as the most frequent. The analysis of anti-COVID19 tweets showed that attacks against vaccine safety were the most important (79.87%) but we detected a new kind of message presenting the vaccine as a means of manipulating the human genetic code (8.1%). We concluded that the antivaccine movement and its tenets have great influence in the COVID-19 negationist movement. We observed a new topic in COVID-19 vaccine hoaxes that must be considered in our fight against misinformation.

Healthcare Professionals' Role in Social Media Public Health Campaigns: Analysis of Spanish Pro Vaccination Campaign on Twitter

The COVID-19 pandemic has generated a great impact worldwide both on the population health but also on an economic and social level. In this health emergency, a key element has been and still is the need for information, which has become a daily concern for many people. Social media represent powerful tools for searching and gathering health-related information, thus becoming a new place where health authorities need to be present to disseminate information of preventive measures like vaccines against COVID-19, as well as try to block information against these public health measures. The main goal of this study was to analyze the role that healthcare professionals have in Twitter to support the campaign of public institutions on vaccination against COVID-19. To address this study, an analysis of the messages sent on Twitter containing the hashtag #yomevacuno, between 12 December 2020 was developed using the NodeXL software (Social Media Research Foundation, Redwood, CA, USA), focusing on content analysis of tweets and users' accounts to identify healthcare professionals. The results show that healthcare professionals represent only 11.38% of users, being responsible for 6.35% of impressions generated by the network #yomevacuno. We can observe that traffic information generated by healthcare professionals is not significant in comparison with institutions (p = 0.633), but it is compared to common users (p = 0.0014). The most active healthcare professionals were pharmacists (40.17%), nurses (27.17%), and physicians (12.14%). Their activity (90.43% of messages) was mainly focused on sharing messages generated by other users' accounts. From original content generated by healthcare professionals, only 78.95% had a favorable storytelling on the vaccine, but without sharing information about vaccines or vaccination. As a conclusion for this study, the participation of healthcare professionals in the dissemination and generation of information within the #yomevacuno communication strategy, led by the Spanish Ministry of Health, has been scarce. We emphasize the need to enhance communication skills in social networks to support public health campaigns through these increasingly important social media.

Citizen journalism practices during COVID-19 in spotlight: influence of user-generated contents about economic policies in perceiving government performance

Purpose

Citizen journalism practices through social networking sites are increasingly becoming an imperative source of public opinion formation. Given the increase in the volume of information sharing on social media during COVID-19, this study aims to grasp the largely unknown interaction of the individual’s trust in citizen journalism practices and public perception formulation. Drawing on this idea, the study has twofold objectives: first, to examine the influence of user-generated information about economic policies of government during COVID-19 as the antecedent of public perception about government performance and second, to identify the moderating role of trust in citizen journalism practices during COVID-19 through social networking sites.

Design/methodology/approach

The study used a survey method and a sample of 464 adults were collected through an online administrated questionnaire.

Findings

The findings specify that user-generated content that is pro-government economic policies during COVID-19 positively influenced the perception of government performance. On the other hand, user-generated information that criticized government economic policies had a negative influence on public perception.

Originality/value

This study seeks to intensify the understudied phenomenon of how nature and source of the information could interact to influence one’s information processing during a crisis such as pandemic COVID-19. Furthermore, only a little research has been conducted in this area focusing on two mechanisms, namely; citizen journalism and trust in social media user-generated information about prevailing economic insecurities during crisis provided through citizen journalism.

Patterns of Media Use, Strength of Belief in COVID-19 Conspiracy Theories, and the Prevention of COVID-19 From March to July 2020 in the United States: Survey Study

BACKGROUND

Holding conspiracy beliefs regarding the COVID-19 pandemic in the United States has been associated with reductions in both actions to prevent the spread of the infection (eg, mask wearing) and intentions to accept a vaccine when one becomes available. Patterns of media use have also been associated with acceptance of COVID-19 conspiracy beliefs. Here we ask whether the type of media on which a person relies increased, decreased, or had no additional effect on that person's COVID-19 conspiracy beliefs over a 4-month period.

OBJECTIVE

We used panel data to explore whether use of conservative and social media in the United States, which were previously found to be positively related to holding conspiracy beliefs about the origins and prevention of COVID-19, were associated with a net increase in the strength of those beliefs from March to July of 2020. We also asked whether mainstream news sources, which were previously found to be negatively related to belief in pandemic-related conspiracies, were associated with a net decrease in the strength of such beliefs over the study period. Additionally, we asked whether subsequent changes in pandemic conspiracy beliefs related to the use of media were also related to subsequent mask wearing and vaccination intentions.

METHODS

A survey that we conducted with a national US probability sample in March of 2020 and again in July with the same 840 respondents assessed belief in pandemic-related conspiracies, use of various types of media information sources, actions taken to prevent the spread of the disease and intentions to vaccinate, and various demographic characteristics. Change across the two waves was analyzed using path analytic techniques.

RESULTS

We found that conservative media use predicted an increase in conspiracy beliefs (β=.17, 99% CI .10-.25) and that reliance on mainstream print predicted a decrease in their belief (β=-.08, 99% CI -.14 to -.02). Although many social media platforms reported downgrading or removing false or misleading content, ongoing use of such platforms by respondents predicted growth in conspiracy beliefs as well (β=.072, 99% CI .018-.123). Importantly, conspiracy belief changes related to media use between the two waves of the study were associated with the uptake of mask wearing and changes in vaccination intentions in July. Unlike other media, use of mainstream broadcast television predicted greater mask wearing (β=.17, 99% CI .09-.26) and vaccination intention (β=.08, 95% CI .02-.14), independent of conspiracy beliefs.

CONCLUSIONS

The findings point to the need for greater efforts on the part of commentators, reporters, and guests on conservative media to report verifiable information about the pandemic. The results also suggest that social media platforms need to be more aggressive in downgrading, blocking, and counteracting claims about COVID-19 vaccines, claims about mask wearing, and conspiracy beliefs that have been judged problematic by public health authorities.

Assessment of the Effectiveness of Identity-Based Public Health Announcements in Increasing the Likelihood of Complying With COVID-19 Guidelines: Randomized Controlled Cross-sectional Web-Based Study

Background

Public health campaigns aimed at curbing the spread of COVID-19 are important in reducing disease transmission, but traditional information-based campaigns have received unexpectedly extreme backlash.

Objective

This study aimed to investigate whether customizing of public service announcements (PSAs) providing health guidelines to match individuals’ identities increases their compliance.

Methods

We conducted a within- and between-subjects, randomized controlled cross-sectional, web-based study in July 2020. Participants viewed two PSAs: one advocating wearing a mask in public settings and one advocating staying at home. The control PSA only provided information, and the treatment PSAs were designed to appeal to the identities held by individuals; that is, either a Christian identity or an economically motivated identity. Participants were asked about their identity and then provided a control PSA and treatment PSA matching their identity, in random order. The PSAs were of approximately 100 words.

Results

We recruited 300 social media users from Amazon Mechanical Turk in accordance with usual protocols to ensure data quality. In total, 8 failed the data quality checks, and the remaining 292 were included in the analysis. In the identity-based PSA, the source of the PSA was changed, and a phrase of approximately 12 words relevant to the individual’s identity was inserted. A PSA tailored for Christians, when matched with a Christian identity, increased the likelihood of compliance by 12 percentage points. A PSA that focused on economic values, when shown to individuals who identified as economically motivated, increased the likelihood of compliance by 6 points.

Conclusions

Using social media to deliver COVID-19 public health announcements customized to individuals’ identities is a promising measure to increase compliance with public health guidelines.

Trial Registration

ISRCTN Registry 22331899; https://www.isrctn.com/ISRCTN22331899.

Impact of a Serious Game (Escape COVID-19) on the Intention to Change COVID-19 Control Practices Among Employees of Long-term Care Facilities: Web-Based Randomized Controlled Trial

BACKGROUND

Most residents of long-term care facilities (LTCFs) are at high risk of complications and death following SARS-CoV-2 infection. In these facilities, viral transmission can be facilitated by shortages of human and material resources, which can lead to suboptimal application of infection prevention and control (IPC) procedures. To improve the dissemination of COVID-19 IPC guidelines, we developed a serious game called "Escape COVID-19" using Nicholson's RECIPE for meaningful gamification, as engaging serious games have the potential to induce behavioral change.

OBJECTIVE

As the probability of executing an action is strongly linked to the intention of performing it, the objective of this study was to determine whether LTCF employees were willing to change their IPC practices after playing "Escape COVID-19."

METHODS

This was a web-based, triple-blind, randomized controlled trial, which took place between November 5 and December 4, 2020. The health authorities of Geneva, Switzerland, asked the managers of all LTCFs under their jurisdiction to forward information regarding the study to all their employees, regardless of professional status. Participants were unaware that they would be randomly allocated to one of two different study paths upon registration. In the control group, participants filled in a first questionnaire designed to gather demographic data and assess baseline knowledge before accessing regular online IPC guidelines. They then answered a second questionnaire, which assessed their willingness to change their IPC practices and identified the reasons underlying their decision. They were then granted access to the serious game. Conversely, the serious game group played "Escape COVID-19" after answering the first questionnaire but before answering the second one. This group accessed the control material after answering the second set of questions. There was no time limit. The primary outcome was the proportion of LTCF employees willing to change their IPC practices. Secondary outcomes included the factors underlying participants' decisions, the domains these changes would affect, changes in the use of protective equipment items, and attrition at each stage of the study.

RESULTS

A total of 295 answer sets were analyzed. Willingness to change behavior was higher in the serious game group (82% [119/145] versus 56% [84/150]; P<.001), with an odds ratio of 3.86 (95% CI 2.18-6.81; P<.001) after adjusting for professional category and baseline knowledge, using a mixed effects logistic regression model with LTCF as a random effect. For more than two-thirds (142/203) of the participants, the feeling of playing an important role against the epidemic was the most important factor explaining their willingness to change behavior. Most of the participants unwilling to change their behavior answered that they were already applying all the guidelines.

CONCLUSIONS

The serious game "Escape COVID-19" was more successful than standard IPC material in convincing LTCF employees to adopt COVID-19-safe IPC behavior.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/25595.

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.

Towards understanding a football club’s social media network: an exploratory case study of Manchester United

Purpose

The purpose of this work is to study how different stakeholders of a football club engage with interactions online through Twitter. It analyses the football club’s Twitter network to discover influential actors and the topic of interest in their online communication.

Design/methodology/approach

The authors analysed the social networks derived from over two million tweets collected during football matches played by Manchester United. The authors applied social network analysis to discover influencers and sub-communities and performed content analysis on the most popular tweets of the prominent influencers.

Findings

Sub-communities can be formed around current affairs that are irrelevant to football, perhaps due to opportunistic attempts of using the large networks and massive attention during football matches to disseminate information. Furthermore, the popularity of tweets featuring different topics depends on the types of influencers involved.

Practical implications

The methods can help football clubs develop a deeper understanding of their online social communities. The findings can also inform football clubs on how to optimise their communication strategies by using various influencers.

Originality/value

Compared to previous research, the authors discovered a wide range of influencers and denser networks characterised by a smaller number of large clusters. Interestingly, this study also found that bots appeared to become influential within the network.

Characterization of Vaccine Tweets During the Early Stage of the COVID-19 Outbreak in the United States: Topic Modeling Analysis

BACKGROUND

During the early stages of the COVID-19 pandemic, developing safe and effective coronavirus vaccines was considered critical to arresting the spread of the disease. News and social media discussions have extensively covered the issue of coronavirus vaccines, with a mixture of vaccine advocacies, concerns, and oppositions.

OBJECTIVE

This study aimed to uncover the emerging themes in Twitter users' perceptions and attitudes toward vaccines during the early stages of the COVID-19 outbreak.

METHODS

This study employed topic modeling to analyze tweets related to coronavirus vaccines at the start of the COVID-19 outbreak in the United States (February 21 to March 20, 2020). We created a predefined query (eg, "COVID" AND "vaccine") to extract the tweet text and metadata (number of followers of the Twitter account and engagement metrics based on likes, comments, and retweeting) from the Meltwater database. After preprocessing the data, we tested Latent Dirichlet Allocation models to identify topics associated with these tweets. The model specifying 20 topics provided the best overall coherence, and each topic was interpreted based on its top associated terms.

RESULTS

In total, we analyzed 100,209 tweets containing keywords related to coronavirus and vaccines. The 20 topics were further collapsed based on shared similarities, thereby generating 7 major themes. Our analysis characterized 26.3% (26,234/100,209) of the tweets as News Related to Coronavirus and Vaccine Development, 25.4% (25,425/100,209) as General Discussion and Seeking of Information on Coronavirus, 12.9% (12,882/100,209) as Financial Concerns, 12.7% (12,696/100,209) as Venting Negative Emotions, 9.9% (9908/100,209) as Prayers and Calls for Positivity, 8.1% (8155/100,209) as Efficacy of Vaccine and Treatment, and 4.9% (4909/100,209) as Conspiracies about Coronavirus and Its Vaccines. Different themes demonstrated some changes over time, mostly in close association with news or events related to vaccine developments. Twitter users who discussed conspiracy theories, the efficacy of vaccines and treatments, and financial concerns had more followers than those focused on other vaccine themes. The engagement level-the extent to which a tweet being retweeted, quoted, liked, or replied by other users-was similar among different themes, but tweets venting negative emotions yielded the lowest engagement.

CONCLUSIONS

This study enriches our understanding of public concerns over new vaccines or vaccine development at early stages of the outbreak, bearing implications for influencing vaccine attitudes and guiding public health efforts to cope with infectious disease outbreaks in the future. This study concluded that public concerns centered on general policy issues related to coronavirus vaccines and that the discussions were considerably mixed with political views when vaccines were not made available. Only a small proportion of tweets focused on conspiracy theories, but these tweets demonstrated high engagement levels and were often contributed by Twitter users with more influence.

Applying and Understanding an Advanced, Novel Deep Learning Approach: A Covid 19, Text Based, Emotions Analysis Study

The pandemic COVID 19 has altered individuals' daily lives across the globe. It has led to preventive measures such as physical distancing to be imposed on individuals and led to terms such as 'lockdown,' 'emergency,' or curfew' to emerge in various countries. It has affected society, not only physically and financially, but in terms of emotional wellbeing as well. This distress in the human emotional quotient results from multiple factors such as financial implications, family member's behavior and support, country-specific lockdown protocols, media influence, or fear of the pandemic. For efficient pandemic management, there is a need to understand the emotional variations among individuals, as this will provide insights into public sentiment towards various government pandemic management policies. From our investigations, it was found that individuals have increasingly used different microblogging platforms such as Twitter to remain connected and express their feelings and concerns during the pandemic. However, research in the area of expressed emotional wellbeing during COVID 19 is still growing, which motivated this team to form the aim: To identify, explore and understand globally the emotions expressed during the earlier months of the pandemic COVID 19 by utilizing Deep Learning and Natural language Processing (NLP). For the data collection, over 2 million tweets during February-June 2020 were collected and analyzed using an advanced deep learning technique of Transfer Learning and Robustly Optimized BERT Pretraining Approach (RoBERTa). A Reddit-based standard Emotion Dataset by Crowdflower was utilized for transfer learning. Using RoBERTa and the collated Twitter dataset, a multi-class emotion classifier system was formed. With the implemented methodology, a tweet classification accuracy of 80.33% and an average MCC score of 0.78 was achieved, improving the existing AI-based emotion classification methods. This study explains the novel application of the Roberta model during the pandemic that provided insights into changing emotional wellbeing over time of various citizens worldwide. It also offers novelty for data mining and analytics during this challenging, pandemic era. These insights can be beneficial for formulating effective pandemic management strategies and devising a novel, predictive strategy for the emotional well-being of an entire country's citizens when facing future unexpected exogenous shocks.

A Serious Game Designed to Promote Safe Behaviors Among Health Care Workers During the COVID-19 Pandemic: Development of "Escape COVID-19"

BACKGROUND

As many countries fear and even experience the emergence of a second wave of COVID-19, reminding health care workers (HCWs) and other hospital employees of the critical role they play in preventing SARS-CoV-2 transmission is more important than ever. Building and strengthening the intrinsic motivation of HCWs to apply infection prevention and control (IPC) guidelines to avoid contaminating their colleagues, patients, friends, and relatives is a goal that must be energetically pursued. A high rate of nosocomial infections during the first COVID-19 wave was detected by IPC specialists and further cemented their belief in the need for an engaging intervention that could improve compliance with COVID-19 safe behaviors.

OBJECTIVE

Our aim was to develop a serious game that would promote IPC practices with a specific focus on COVID-19 among HCWs and other hospital employees.

METHODS

The first 3 stages of the SERES framework were used to develop this serious game. A brainswarming session between developers and IPC specialists was used to identify the target audience and acquisition objectives. Nicholson's RECIPE mnemonic (reflection, engagement, choice, information, play, exposition) for meaningful gamification was used to guide the general design. A common and simple terminology was used to suit the broad target audience. The game was tested on various platforms (smartphones, tablets, laptops, desktop computers) by different users during each development loop and before its final release.

RESULTS

The game was designed to target all hospital staff who could be in direct contact with patients within the Geneva University Hospitals. In total, 10 acquisition objectives were defined by IPC specialists and implemented into the game according to the principles of meaningful gamification. A simple storyboard was first created using Microsoft PowerPoint and was progressively refined through multiple iteration loops. Articulate Storyline was then used to create two successive versions of the actual game. In the final version, a unique graphic atmosphere was created with help from a professional graphic designer. Feedback mechanisms were used extensively throughout the game to strengthen key IPC messages.

CONCLUSIONS

The SERES framework was successfully used to create "Escape COVID-19," a serious game designed to promote safe IPC practices among HCWs and other hospital employees during the COVID-19 pandemic. This game can be obtained free of charge for research and educational purposes. A SCORM (shareable content object reference model) package is available to facilitate results and completion tracking on most current learning management systems.

A Social Network Analysis of Tweets Related to Masks during the COVID-19 Pandemic

BACKGROUND

High compliance in wearing a mask is a crucial factor for stopping the transmission of COVID-19. Since the beginning of the pandemic, social media has been a key communication channel for citizens. This study focused on analyzing content from Twitter related to masks during the COVID-19 pandemic.

METHODS

Twitter data were collected using the keyword "mask" from 27 June 2020 to 4 July 2020. The total number of tweets gathered were n = 452,430. A systematic random sample of 1% (n = 4525) of tweets was analyzed using social network analysis. NodeXL (Social Media Research Foundation, California, CA, USA) was used to identify users ranked influential by betweenness centrality and was used to identify key hashtags and content.

RESULTS

The overall shape of the network resembled a community network because there was a range of users conversing amongst each other in different clusters. It was found that a range of accounts were influential and/or mentioned within the network. These ranged from ordinary citizens, politicians, and popular culture figures. The most common theme and popular hashtags to emerge from the data encouraged the public to wear masks.

CONCLUSION

Towards the end of June 2020, Twitter was utilized by the public to encourage others to wear masks and discussions around masks included a wide range of users.