Data-driven analytics of COVID-19 'infodemic'.

The rampant of COVID-19 infodemic has almost been simultaneous with the outbreak of the pandemic. Many concerted efforts are made to mitigate its negative effect to information credibility and data legitimacy. Existing work mainly focuses on fact-checking algorithms or multi-class labeling models that are less aware of the intrinsic characteristics of the language. Nor is it discussed how such representations can account for the common psycho-socio-behavior of the information consumers. This work takes a data-driven analytical approach to (1) describe the prominent lexical and grammatical features of COVID-19 misinformation; (2) interpret the underlying (psycho-)linguistic triggers in terms of sentiment, power and activity based on the affective control theory; (3) study the feature indexing for anti-infodemic modeling. The results show distinct language generalization patterns of misinformation of favoring evaluative terms and multimedia devices in delivering a negative sentiment. Such appeals are effective to arouse people's sympathy toward the vulnerable community and foment their spreading behavior.

From strategic depiction of conspiracies to conspiracy theories RT's and Sputnik's representations of coronavirus infodemic

Our study focuses on the coverage of coronavirus-related conspiracies/conspiracy theories published in spring 2020 (n = 146) in Anglophone media outlets RT and Sputnik that are financed by the Russian government. In our analysis we rely on a semiotic approach to strategic (conspiracy) narratives. Our study demonstrates a significant shift in the representation of conspiracies: instead of the depiction of malicious acts of secret grouping, RT and Sputnik narrate about alarming effects of conspiracy theories. Coronavirus-related conspiracy theories are represented as a means that the US is using in blame games against China and Russia, as well as a propaganda-tool for scaring the Western audience. © 2022 John Benjamins Publishing Company.

Health misinformation and freedom of expression: considerations for policymakers.

Health misinformation, most visibly following the COVID-19 infodemic, is an urgent threat that hinders the success of public health policies. It likely contributed, and will continue to contribute, to avoidable deaths. Policymakers around the world are being pushed to tackle this problem. Legislative acts have been rolled out or announced in many countries and at the European Union level. The goal of this paper is not to review particular legislative initiatives, or to assess the impact and efficacy of measures implemented by digital intermediaries, but to reflect on the high constitutional and ethical stakes involved in tackling health misinformation through speech regulation. Our findings suggest that solutions focused on regulating speech are likely to encounter significant constraints, as policymakers grasp with the limitations imposed by freedom of expression and ethical considerations. Solutions focused on empowering individuals - such as media literacy initiatives, fact-checking or credibility labels - are one way to avoid such hurdles.

Equipping Students and Beyond with Sound COVID-19 Knowledge to Survive and Thrive Despite the Pandemic.

The COVID-19 pandemic necessitated the understanding of the infodemic for making informed decisions. Limiting the spread of health misinformation and disinformation was the primary goal of the health informatics project. The project became the recipient of the ASIS&T "Chapter Innovation of the Year Award 2021". A repertoire of online and offline initiatives was carried out with 9 well-researched videos for promoting health informatics. Since August 2021, thousands of academics, librarians, teachers, parents, and students from 16 countries and regions were invited to be science communicators to create and disseminate accurate health information in their areas through an international digital story writing competition. In this paper, we will discuss the strategies of responding to the information crisis, including employing interventions that protect against the infodemic and mitigate its harmful effects, to strengthen the resilience of individuals and communities in dealing with it in an information-resilient society.

Susceptibility to COVID-19 Nutrition Misinformation and Eating Behavior Change during Lockdowns: An International Web-Based Survey.

To understand the susceptibility to nutrition-health misinformation related to preventing, treating, or mitigating the risk of COVID-19 during the initial lockdowns around the world, the present international web-based survey study (15 April-15 May 2020) gauged participants' (n = 3707) level of nutrition-health misinformation discernment by presenting them with 25 statements (including unfounded or unproven claims circulated at the time), alongside the influence of information sources of varying quality on the frequency of changes in their eating behavior and the extent of misinformation held, depending on the source used for such changes. Results revealed widespread misinformation about food, eating, and health practices related to COVID-19, with the 25 statements put to participants receiving up to 43% misinformed answers (e.g., 'It is safe to eat fruits and vegetables that have been washed with soap or diluted bleach'). Whereas higher quality information sources (nutrition scientists, nutrition professionals) had the biggest influence on eating behavior change, we found greater misinformation susceptibility when relying on poor quality sources for changing diet. Appropriate discernment of misinformation was weakest amongst participants who more frequently changed their eating behavior because of information from poor quality sources, suggesting disparities in the health risks/safety of the changes performed.

Topic Modeling for Tracking COVID-19 Communication on Twitter

In this study, we analyze the trends of COVID-19 related communication in Croatian language on Twitter. First, we prepare a dataset of 147,028 tweets about COVID-19 posted during the first three waves of the pandemic, and then perform an analysis in three steps. In the first step, we train the LDA model and calculate the coherence values of the topics. We identify seven topics and report the ten most frequent words for each topic. In the second step, we analyze the proportion of tweets in each topic and report how these trends change over time. In the third step, we study spreading properties for each topic. The results show that all seven topics are evenly distributed across the three pandemic waves. The topic “vaccination” stands out with the change in percentage from 14.6% tweets in the first wave to 25.7% in the third wave. The obtained results contribute to a better understanding of pandemic communication in social media in Croatia. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Health Information Crisis during COVID-19 in the South Asian Region: Challenges, Experiences, Resilience, and Collaborative Efforts.

The fight against the COVID-19 pandemic is as much an information war as it is a medical war. Members from South Asia and the Asia Pacific countries share their experiences and challenges faced with collaborative responses for the ASIS&T Special Chapter funded project on "Dealing with COVID-19 and saving people's lives in South Asia (SA) areas & beyond-A Health Informatics Promotion Project" awarded to the South Asia Chapter in 2021. The panel discusses the challenges faced within the context of geopolitical, socio-economic, religious, and cultural conditions prevalent within their countries. In the first 40 minutes, panel members narrate their own experiences by sharing their personal stories about this collaborative project and share the challenges of content creation and promotion from within the context of their respective countries. The next 30 minutes will be facilitated by the panel chair inviting a discussion between panel members and the audience to engage and come up with innovative ideas, discuss challenges in creating multilingual content and suggestions for improving the project outcome as well as shed light on initiating future health informatics project in similar regions. The last 20 minutes will culminate with the summarization of these collaborative experiences.

Pathway linking health information behaviors to mental health condition during the COVID-19 infodemic: A moderated mediation analysis.

Background: The COVID-19 outbreak is no longer a pure epidemiological concern but a true digital infodemic. Numerous conflicting information and misinformation occupy online platforms and specifically social media. While we have lived in an infodemic environment for more than 2 years, we are more prone to feel overwhelmed by the information and suffer from long-term mental health problems. However, limited research has concentrated on the cause of these threats, particularly in terms of information processing and the context of infodemic. Objective: This study proposed and tested moderated mediation pathways from two types of health information behaviors (social media engagement and interpersonal communication) on information overload and mental health symptoms-long-term stress. Methods: We conducted a cross-sectional online survey between May and June of 2021 among the Malaysian public. The final sample size was 676 (N = 676). A conceptual model was built to guide the data analysis. We conducted structural equation modeling (SEM), moderation and mediation analyses to examine each direct pathway, moderating and mediating effects. Results: According to the pathway analysis, we found that, during the infodemic period, engaging COVID-19 information on social media positively associated with information overload, but interpersonal communication was negatively related to it. As the proximal outcome, there was also a positive association between information overload and the final outcome, perceived stress. The moderation analysis only reported one significant interaction: risk perception weakened the association between social media engagement and information overload. A conditional indirect effect was demonstrated and the indirect associated between social media engagement and perceived stress mediated through information overload was further moderated by COVID-19 risk perception. Conclusion: This research offers new grounds for understanding health information behaviors and their consequences in the COVID-19 infodemic. We particularly highlighted the distinct functions of health information behaviors in causing information overload, as well as the importance of personal health belief in this process. Our proposed model contributes to the strategies of developing health messaging strategies that may be utilized by public health researchers and health educators in the future.

The COVID-19 Infodemic: Misinformation About Health on Social Media in Istanbul

Misinformation and conspiracy theories can spread as quickly as the COVID-19 pathogen itself. The infodemic, which describes false or misleading information about this recent epidemic on the internet, has become a serious problem all over the world, and has been declared as an "enemy" by the World Health Organization. In this sense, in order to combat the epidemic, it becomes important to reveal the nuances of COVID-19 related infodemic available on the internet. Particularly, internet users in Turkey are increasingly utilizing social media -a platform synonymous with misinformation- to access news coverage regarding the pandemic (World Health Organization, 2020). In this quantitative study focusing on the city of Istanbul (n=399), which is at the epicenter of the outbreak in Turkey, the social media usage of individuals, their trust in these platforms, exposure to misinformation and conspiracy theories, and fact-checking behaviors were examined. Our results indicate that participants tended to believe in misinformation and conspiracy theories rather than confirming information through fact-checking platforms. Nearly half of all participants believed at least one of four widespread conspiracy theories about the virus. Moreover, when fact-checking did identify misinformation, the participants' trust in social media showed a slight decrease. Based on these findings, our study proposes a comprehensive model for pandemic-related trust, misinformation, conspiracy theories, and fact-checking factors on digital platforms.

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.

How Official Social Media Affected the Infodemic among Adults during the First Wave of COVID-19 in China.

The COVID-19 pandemic has demonstrated that social media can impact society both positively (e.g., keeping citizens connected and informed) and negatively (e.g., the deliberate spreading of misinformation). This study aims to examine the underlying mechanisms of the relationship between official social media accounts and the infodemic, experienced during the first wave of COVID-19 in China. A theoretical model is proposed to examine how official social media accounts affected the infodemic during this period. In total, 1398 questionnaire responses were collected via WeChat and Tencent QQ, two leading Chinese social media platforms. Data analysis was conducted using Partial Lease Squares Structural Equation Modeling (PLS-SEM), moderation effect analysis, and mediation effect analysis. Results indicate that the Information Quality (IQ) of Official social media accounts (ß = -0.294, p < 0.001) has a significant negative effect on the infodemic. Mediation effect analysis revealed that both social support (ß = -0.333, 95% Boot CI (-0.388, -0.280)) and information cascades (ß = -0.189, 95% Boot CI (-0.227, -0.151)) mediate the relationship between IQ and the infodemic. Moderation effect analysis shows that private social media usage (F = 85.637, p < 0.001) positively moderates the relationship between IQ and the infodemic, while health literacy has a small negative moderation effect on the relationship between IQ and the infodemic. Our findings show that, in the context of Chinese media, official social media accounts act as a major source of information for influencing the infodemic through increasing social support and reducing information cascades for citizens.

Open Debates Conducive for Vaccination Rate Flatlines: A Scoping Review and Convergent Cross Mapping.

COVID-19 pandemic is fueling digital health transformation-accelerating innovations of digital health services, surveillance, and interventions, whereas hastening social contagion of deliberate infodemic. The USA and many other countries are experiencing a resurgent wave of the COVID-19 pandemic with vaccination rate slowdown, making policymaking fraught with challenges. Political leaders and scientists have publicly warned of a "pandemic of the unvaccinated," reinforcing their calls for citizens to get jabs. However, some scientists accused elites of stigmatizing the unvaccinated people and undermining the moral pillars of public health. Following the PRISMA-ScR guidelines, we first reviewed the nuances of stakeholders involved in the ongoing debates and revealed the potential consequences of divisive pronouncements to provide perspectives to reframe extensible discussions. Then, we employed the convergent cross mapping (CCM) model to reveal the uncharted knock-on effects of the contentious tsunami in a stakeholders-oriented policymaking framework, coupled with rich metadata from the GDELT project and Google Trends. Our experimental findings suggest that current news coverage may shape the mindsets of the vaccines against the unvaccinated, thereby exacerbating the risk of dualistic antagonism in algorithmically infused societies. Finally, we briefly summarized how open debates are conducive to increasing vaccination rates and bolstering the outcomes of impending policies for pandemic preparedness.

COS2: Detecting Large-Scale COVID-19 Misinformation in Social Networks

The ongoing COVID-19 pandemic is bringing an “infodemic” on social media. Simultaneously, the huge volume of misinformation (such as rumors, fake news, spam posts, etc.) is scattered in every corner of people’s social life. Traditional misinformation detection methods typically focus on centralized offline processing, that is, they process pandemic-related social data by deploying the model in a single local server. However, such processing incurs extremely long latency when detecting social misinformation related to COVID-19, and cannot handle large-scale social misinformation. In this paper, we propose COS2, a distributed and scalable system that supports large-scale COVID-19-related social misinformation detection. COS2 is able to automatically deploy many groups to distribute deep learning models in scalable cloud servers, process large-scale COVID-19-related social data in various groups, and efficiently detect COVID-19-related tweets with low latency. © 2022, Springer Nature Switzerland AG.

Perspectives on Mass Media and Governmental Measures during the 2020 COVID-19 Pandemic in a Romanian Sample of Healthcare Practitioners.

OBJECTIVE: Along with the rapid spread of the COVID-19 pandemic around the globe, a proliferation of mass media information exposed the population to an infodemic with various implications documented worldwide. The present study analyzed Romanian healthcare practitioners' (HCPs) appraisal of COVID-19 mass media information and governmental measures throughout 2020, ranking vaccination priorities and moral values. METHODS: 97 HCP completed a cross-sectional survey with items referring to the COVID-19 pandemic in 2020. RESULTS: Findings were consistent with other studies, indicating an overall negative appraisal of mass media information, which predicted anxiety and relaxation difficulties. Unlike other studies, our sample reported a moderate level of satisfaction with official measures in 2020, which was not related to their view on mass media information. The ranking of population categories in the vaccination order showed similarities with the governmental vaccination program in 2021. Despite placing freedom third after health and love in the hierarchy of values, HCPs showed a high tendency of limiting individual liberty for the common good. CONCLUSIONS: Results showed a dissociation between the overall negative appraisal of mass media information and the satisfaction with governmental measures in 2020. Romanian HCPs shared a secular perspective on moral values and assumed an authoritarian position.

The causes, impacts and countermeasures of COVID-19 "Infodemic": A systematic review using narrative synthesis.

An unprecedented infodemic has been witnessed to create massive damage to human society. However, it was not thoroughly investigated. This systematic review aims to (1) synthesize the existing literature on the causes and impacts of COVID-19 infodemic; (2) summarize the proposed strategies to fight with COVID-19 infodemic; and (3) identify the directions for future research. A systematic literature search following the PRISMA guideline covering 12 scholarly databases was conducted to retrieve various types of peer-reviewed articles that reported causes, impacts, or countermeasures of the infodemic. Empirical studies were assessed for risk of bias using the Mixed-Methods Appraisal Tool. A coding theme was iteratively developed to categorize the causes, impacts, and countermeasures found from the included studies. Social media usage, low level of health/eHealth literacy, and fast publication process and preprint service are identified as the major causes of the infodemic. Besides, the vicious circle of human rumor-spreading behavior and the psychological issues from the public (e.g., anxiety, distress, fear) emerges as the characteristic of the infodemic. Comprehensive lists of countermeasures are summarized from different perspectives, among which risk communication and consumer health information need/seeking are of particular importance. Theoretical and practical implications are discussed and future research directions are suggested.

Flow of online misinformation during the peak of the COVID-19 pandemic in Italy.

The COVID-19 pandemic has impacted on every human activity and, because of the urgency of finding the proper responses to such an unprecedented emergency, it generated a diffused societal debate. The online version of this discussion was not exempted by the presence of misinformation campaigns, but, differently from what already witnessed in other debates, the COVID-19 -intentional or not- flow of false information put at severe risk the public health, possibly reducing the efficacy of government countermeasures. In this manuscript, we study the effective impact of misinformation in the Italian societal debate on Twitter during the pandemic, focusing on the various discursive communities. In order to extract such communities, we start by focusing on verified users, i.e., accounts whose identity is officially certified by Twitter. We start by considering each couple of verified users and count how many unverified ones interacted with both of them via tweets or retweets: if this number is statically significant, i.e. so great that it cannot be explained only by their activity on the online social network, we can consider the two verified accounts as similar and put a link connecting them in a monopartite network of verified users. The discursive communities can then be found by running a community detection algorithm on this network. We observe that, despite being a mostly scientific subject, the COVID-19 discussion shows a clear division in what results to be different political groups. We filter the network of retweets from random noise and check the presence of messages displaying URLs. By using the well known browser extension NewsGuard, we assess the trustworthiness of the most recurrent news sites, among those tweeted by the political groups. The impact of low reputable posts reaches the 22.1% in the right and center-right wing community and its contribution is even stronger in absolute numbers, due to the activity of this group: 96% of all non reputable URLs shared by political groups come from this community. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1140/epjds/s13688-021-00289-4.