COVID-19 Misinformation Research Articles

COVID-19 Misinformation and Social Network Crowdfunding: Cross-sectional Study of Alternative Treatments and Antivaccine Mandates.

BackgroundCrowdfunding is increasingly used to offset the financial burdens of illness and health care. In the era of the COVID-19 pandemic and associated infodemic, the role of crowdfunding to support controversial COVID-19 stances is unknown.ObjectiveWe sought to examine COVID-19–related crowdfunding focusing on the funding of alternative treatments not endorsed by major medical entities, including campaigns with an explicit antivaccine, antimask, or antihealth care stances.MethodsWe performed a cross-sectional analysis of GoFundMe campaigns for individuals requesting donations for COVID-19 relief. Campaigns were identified by key word and manual review to categorize campaigns into “Traditional treatments,” “Alternative treatments,” “Business-related,” “Mandate,” “First Response,” and “General.” For each campaign, we extracted basic narrative, engagement, and financial variables. Among those that were manually reviewed, the additional variables of “mandate type,” “mandate stance,” and presence of COVID-19 misinformation within the campaign narrative were also included. COVID-19 misinformation was defined as “false or misleading statements,” where cited evidence could be provided to refute the claim. Descriptive statistics were used to characterize the study cohort.ResultsA total of 30,368 campaigns met the criteria for final analysis. After manual review, we identified 53 campaigns (0.17%) seeking funding for alternative medical treatment for COVID-19, including popularized treatments such as ivermectin (n=14, 26%), hydroxychloroquine (n=6, 11%), and vitamin D (n=4, 7.5%). Moreover, 23 (43%) of the 53 campaigns seeking support for alternative treatments contained COVID-19 misinformation. There were 80 campaigns that opposed mandating masks or vaccination, 48 (60%) of which contained COVID-19 misinformation. Alternative treatment campaigns had a lower median amount raised (US $1135) compared to traditional (US $2828) treatments (P<.001) and a lower median percentile of target achieved (11.9% vs 31.1%; P=.003). Campaigns for alternative treatments raised substantially lower amounts (US $115,000 vs US $52,715,000, respectively) and lower proportions of fundraising goals (2.1% vs 12.5%) for alternative versus conventional campaigns. The median goal for campaigns was significantly higher (US $25,000 vs US $10,000) for campaigns opposing mask or vaccine mandates relative to those in support of upholding mandates (P=.04). Campaigns seeking funding to lift mandates on health care workers reached US $622 (0.15%) out of a US $410,000 goal.ConclusionsA small minority of web-based crowdfunding campaigns for COVID-19 were directed at unproven COVID-19 treatments and support for campaigns aimed against masking or vaccine mandates. Approximately half (71/133, 53%) of these campaigns contained verifiably false or misleading information and had limited fundraising success.International Registered Report Identifier (IRRID)RR2-10.1001/jamainternmed.2019.3330

Investigation of COVID-19 Misinformation in Arabic on Twitter: Content Analysis.

BackgroundThe COVID-19 pandemic has been occurring concurrently with an infodemic of misinformation about the virus. Spreading primarily on social media, there has been a significant academic effort to understand the English side of this infodemic. However, much less attention has been paid to the Arabic side.ObjectiveThere is an urgent need to examine the scale of Arabic COVID-19 disinformation. This study empirically examines how Arabic speakers use specific hashtags on Twitter to express antivaccine and antipandemic views to uncover trends in their social media usage. By exploring this topic, we aim to fill a gap in the literature that can help understand conspiracies in Arabic around COVID-19.MethodsThis study used content analysis to understand how 13 popular Arabic hashtags were used in antivaccine communities. We used Twitter Academic API v2 to search for the hashtags from the beginning of August 1, 2006, until October 10, 2021. After downloading a large data set from Twitter, we identified major categories or topics in the sample data set using emergent coding. Emergent coding was chosen because of its ability to inductively identify the themes that repeatedly emerged from the data set. Then, after revising the coding scheme, we coded the rest of the tweets and examined the results. In the second attempt and with a modified codebook, an acceptable intercoder agreement was reached (Krippendorff α≥.774).ResultsIn total, we found 476,048 tweets, mostly posted in 2021. First, the topic of infringing on civil liberties (n=483, 41.1%) covers ways that governments have allegedly infringed on civil liberties during the pandemic and unfair restrictions that have been imposed on unvaccinated individuals. Users here focus on topics concerning their civil liberties and freedoms, claiming that governments violated such rights following the pandemic. Notably, users denounce government efforts to force them to take any of the COVID-19 vaccines for different reasons. This was followed by vaccine-related conspiracies (n=476, 40.5%), including a Deep State dictating pandemic policies, mistrusting vaccine efficacy, and discussing unproven treatments. Although users tweeted about a range of different conspiracy theories, mistrusting the vaccine’s efficacy, false or exaggerated claims about vaccine risks and vaccine-related diseases, and governments and pharmaceutical companies profiting from vaccines and intentionally risking the general public health appeared the most. Finally, calls for action (n=149, 12.6%) encourage individuals to participate in civil demonstrations. These calls range from protesting to encouraging other users to take action about the vaccine mandate. For each of these categories, we also attempted to trace the logic behind the different categories by exploring different types of conspiracy theories for each category.ConclusionsBased on our findings, we were able to identify 3 prominent topics that were prevalent amongst Arabic speakers on Twitter. These categories focused on violations of civil liberties by governments, conspiracy theories about the vaccines, and calls for action. Our findings also highlight the need for more research to better understand the impact of COVID-19 disinformation on the Arab world.

A scoping review of COVID-19 online mis/disinformation in Black communities.

BackgroundMis/disinformation has reached an epidemic level with the COVID-19 virus and can be largely attributed to the growing digitalization of information and its rapid transmission via social media. Approximately 96% of Canadians and 80% of Americans report encountering COVID-19 dis/misinformation on at least one social media site/app. COVID-19 dis/misinformation promotes scepticism and a lack of confidence in COVID-19 interventions. Black people have been disproportionately affected by the COVID-19 pandemic in terms of negative impacts on their livelihoods and are also more likely to be hesitant to receive the COVID-19 vaccine. Dis/misinformation contributes to high rates of COVID-19 infection and low uptake of COVID-19 vaccination. Hence, the purpose of this scoping review was to map out the nature and extent of current research on COVID-19 disinformation among Blacks in Africa and the African diaspora.MethodsWe searched and reviewed articles from major databases such as MEDLINE, EMBASE, and CINAHL. Our search strategy involved the following concepts: 1) COVID-19, including variants; 2) misinformation, conspiracy theories, and fake news, and modes of misinformation transmission such as social media; and 3) Blacks or people of African descent, or the African diaspora. We retrieved 600 articles that were independently screened by two researchers. We included studies focusing on 1) Black people living inside or outside Africa; and 2) COVID-19 online dis/misinformation among this population. A total of 19 studies fit our inclusion criteria. We used a thematic analysis to analyse qualitative data.ResultsOur findings indicate Black people are accessing and often sharing online disinformation and misinformation primarily through social media platforms such as WhatsApp, Facebook, Twitter, YouTube, and Instagram. Dis/misinformation concerns the origin of COVID-19, transmission, prevention, and treatment of COVID-19, assertions of race immunity to the virus, distrust in government and health organizations, and intervention research and programming.ConclusionsThere is a global paucity of literature addressing COVID-19 online dis/misinformation among Black people. Dis/misinformation can fuel vaccine hesitancy and threaten the goal of herd immunity. Knowledge of the impact and implications of COVID-19 online dis/misinformation is necessary to inform public health interventions in Black communities.

Developing a Digital Technology System to Address COVID-19 Health Needs in Guatemala: A Scientific Diaspora Case Study.

Scientific diasporas are organized groups of professionals who work together to contribute to their country of origin. Since the start of the COVID-19 pandemic in 2020, scientific diasporas around the world have focused their efforts to support the public health response in their countries of origin. As the first cases of COVID-19 were reported in Guatemala in March of 2020, a team of four Guatemalan nationals, residing abroad and in-country, started collaborating to tackle COVID-19 misinformation and issues with healthcare services navigation. Their collaboration was facilitated by FUNDEGUA, a Guatemalan nonprofit, which provided a legal framework to establish partnerships and fundraise. The team created a digital technological system called ALMA (Asistente de Logística Médica Automatizada in Spanish). A female character named ALMA was created to personify the digital information services, through social media profiles, an interactive website, a free national multilingual call center, and an artificial intelligence-based chatbot. More members joined the nascent interdisciplinary diaspora through professional/personal references or social media. ALMA provided a platform for Guatemalan nationals to contribute with their skillset to their country during a global crisis through flexible schedules and short- or long-term involvement. As the team grew, the services for query resolution and information dissemination expanded as well. The ALMA initiative shows that scientific diasporas can provide an avenue for professionals to contribute to Guatemala, regardless of their residence and job commitments.

Using Fuzzy Clustering with Deep Learning Models for Detection of COVID-19 Disinformation

Since the beginning of 2020, the COVID-19 pandemic has killed millions of people around the world, leading to a worldwide panic that has fueled the rapid and widespread dissemination of COVID-19-related disinformation on social media. The phenomenon, described by the World Health Organization (WHO) as an "indodemic" presents a serious challenge to governments and public health authorities, but the spread of misinformation has made human detection less efficient than the rate of spread. While there have been many studies developing automated detection techniques for COVID-19 fake news, the results often refer to high accuracy but rarely to model detection time. This research uses fuzzy theory to extract features and uses multiple deep learning model frameworks to detect Chinese and English COVID-19 misinformation. With the reduction of text features, the detection time of the model is significantly reduced, and the model accuracy does not drop excessively. This study designs two different feature extraction methods based on fuzzy classification and compares the results with different deep learning models. BiLSTM was found to provide the best detection results for COVID-19 misinformation by directly using deep learning models, with 99% accuracy in English and 86% accuracy in Chinese. Applying fuzzy clustering to English COVID-19 fake news data features maintains 99% accuracy while reducing detection time by 10%. For Chinese misinformation, detection time is reduced by 15% at the cost of an 8% drop in accuracy.

Differences in Beliefs and Behaviors Related to COVID-19 Prevention Among Adult Current and Former Smokers and With and Without A Cancer Diagnosis.

PurposeStudy aims included assessing differences in beliefs/behaviors about COVID-19 prevention among current and former smokers with and without cancer.DesignA cross-sectional survey about COVID-19 beliefs/behaviors was administered from June 2020 to January 2021.SettingSurvey conducted online via Qualtrics from June 2020 to January 2021.SubjectsParticipants were current (n = 101) and former (n = 102) smokers with and without cancer.MeasuresQuestions were related to beliefs about efficacy of and engagement in behaviors for COVID-19 prevention.ResultsResults from logistic regressions displayed that individuals with cancer were more likely to indicate using hand sanitizer with at least 60% alcohol was ineffective (OR = .12, 95% CI: [.02, .65]) and avoided public transportation (OR = 1.84, 95% CI: [1.04, 3.28]) compared to those without cancer. Former smokers were more likely to indicate taking vitamin C was effective (OR = .45, 95% CI: [.22, .93]) and rinsing your mouth with salt water (OR = 1.89, 95% CI: [1.02, 3.50]) was ineffective compared to current smokers. Current smokers were more likely to indicate not smoking was effective compared to former smokers (OR = 2.19, 95% CI: [1.13, 4.24]).ConclusionsCounters to COVID-19 misinformation may need to be tailored to different at-risk groups based on differential beliefs and behaviors.

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

BackgroundInfodemic management is an integral part of pandemic management. Ghana Health Services (GHS) together with the UNICEF (United Nations International Children's Emergency Fund) Country Office have developed a systematic process that effectively identifies, analyzes, and responds to COVID-19 and vaccine-related misinformation in Ghana.ObjectiveThis paper describes an infodemic management system workflow based on digital data collection, qualitative methodology, and human-centered systems to support the COVID-19 vaccine rollout in Ghana with examples of system implementation.MethodsThe infodemic management system was developed by the Health Promotion Division of the GHS and the UNICEF Country Office. It uses Talkwalker, a social listening software platform, to collect misinformation on the web. The methodology relies on qualitative data analysis and interpretation as well as knowledge cocreation to verify the findings.ResultsA multi-sectoral National Misinformation Task Force was established to implement and oversee the misinformation management system. Two members of the task force were responsible for carrying out the analysis. They used Talkwalker to find posts that include the keywords related to COVID-19 vaccine–related discussions. They then assessed the significance of the posts on the basis of the engagement rate and potential reach of the posts, negative sentiments, and contextual factors. The process continues by identifying misinformation within the posts, rating the risk of identified misinformation posts, and developing proposed responses to address them. The results of the analysis are shared weekly with the Misinformation Task Force for their review and verification to ensure that the risk assessment and responses are feasible, practical, and acceptable in the context of Ghana.ConclusionsThe paper describes an infodemic management system workflow in Ghana based on qualitative data synthesis that can be used to manage real-time infodemic responses.

Impact of COVID-19 Vaccine Misinformation on Social Media Virality: Content Analysis of Message Themes and Writing Strategies.

BackgroundVaccines serve an integral role in containing pandemics, yet vaccine hesitancy is prevalent globally. One key reason for this hesitancy is the pervasiveness of misinformation on social media. Although considerable research attention has been drawn to how exposure to misinformation is closely associated with vaccine hesitancy, little scholarly attention has been given to the investigation or robust theorizing of the various content themes pertaining to antivaccine misinformation about COVID-19 and the writing strategies in which these content themes are manifested. Virality of such content on social media exhibited in the form of comments, shares, and reactions has practical implications for COVID-19 vaccine hesitancy.ObjectiveWe investigated whether there were differences in the content themes and writing strategies used to disseminate antivaccine misinformation about COVID-19 and their impact on virality on social media.MethodsWe constructed an antivaccine misinformation database from major social media platforms during September 2019-August 2021 to examine how misinformation exhibited in the form of content themes and how these themes manifested in writing were associated with virality in terms of likes, comments, and shares. Antivaccine misinformation was retrieved from two globally leading and widely cited fake news databases, COVID Global Misinformation Dashboard and International Fact-Checking Network Corona Virus Facts Alliance Database, which aim to track and debunk COVID-19 misinformation. We primarily focused on 140 Facebook posts, since most antivaccine misinformation posts on COVID-19 were found on Facebook. We then employed quantitative content analysis to examine the content themes (ie, safety concerns, conspiracy theories, efficacy concerns) and manifestation strategies of misinformation (ie, mimicking of news and scientific reports in terms of the format and language features, use of a conversational style, use of amplification) in these posts and their association with virality of misinformation in the form of likes, comments, and shares.ResultsOur study revealed that safety concern was the most prominent content theme and a negative predictor of likes and shares. Regarding the writing strategies manifested in content themes, a conversational style and mimicking of news and scientific reports via the format and language features were frequently employed in COVID-19 antivaccine misinformation, with the latter being a positive predictor of likes.ConclusionsThis study contributes to a richer research-informed understanding of which concerns about content theme and manifestation strategy need to be countered on antivaccine misinformation circulating on social media so that accurate information on COVID-19 vaccines can be disseminated to the public, ultimately reducing vaccine hesitancy. The liking of COVID-19 antivaccine posts that employ language features to mimic news or scientific reports is perturbing since a large audience can be reached on social media, potentially exacerbating the spread of misinformation and hampering global efforts to combat the virus.

Design Principles for an Educational Intervention Into Online Vaccine Misinformation.

As part of a design-based research effort into disrupting the spread of COVID-19 misinformation, we have iteratively designed, developed, and evaluated a learning intervention intended for public audiences. In this paper we describe the design principles we created to guide our applied research into education on the topic of online misinformation. The six principles guiding our design are: microlearning; equity; relevance and appeal to learners; interventions that do not inadvertently spread misinformation; effective counter messaging; and engagement on an emotional level. These principles are grounded on equitable design, anti-misinformation design, and emotional design.

Indexing theory during an emerging health crisis: how U.S. TV news indexed elite perspectives and amplified COVID-19 misinformation

ABSTRACT This paper applies indexing theory to test whether U.S. television news about COVID-19 covered misinformed elite viewpoints and whether indexing patterns were consistent across networks. We extend theory by investigating an emerging crisis where information was in flux. We conducted a content analysis of U.S. broadcast and cable news coverage of two COVID-19 issues: masks and disinfectants/UV light. Coverage responded to changes in health institution guidance related to mask wearing, but: (a) mentioning partisan elites was related to misleading content, (b) at times mentioning health institutions was related to decreased inclusion of correct information, and (c) at times patterns of indexing differed across networks. Findings suggest that indexing practices may encourage misinformation spread during emerging crises, especially on partisan news.

Covid-19 stigmatization: A systematic literature review.

Covid-19 has severe implications for the emergence of negative stigmatization of specific individuals and community groups. Due to labeling and discrimination, mental attacks cause psychological distress so seriously that it requires proper handling. Therefore, this study aims to conduct a systematic literature review on articles on COVID-19 stigmatization. This paper used descriptive analysis that 248 articles are from the Scopus database obtained by keyword Covid-19 stigmatization in the 2020–2021 time span were then processed and visualized using the Vosviewer software. The results reveal the three most dominant concepts studied: anxiety, isolation, and knowledge. The Covid-19 stigma arises due to low public knowledge, widespread Covid-19 disinformation, and lack of trust in the government. This research contributes to a description of the root causes and adverse effects of stigmatization during Covid-19 to help formulate recommendations for preventive and treatment actions that can be taken. Meanwhile, the limitation of this research is that the articles reviewed are only sourced from Scopus, so they do not have comparative data. Therefore, future studies require using a comparative analysis approach that uses a Web of Science (WoS) database.

Let’s verify and rectify! Examining the nuanced influence of risk appraisal and norms in combatting misinformation

Mounting concerns about COVID-19 misinformation and its insidious fallout drive the search for viable solutions. Both scholarly and practical efforts have turned toward raising risk appraisal of misinformation and motivating verification and debunking behaviors. However, individuals remain reluctant to verify and correct misinformation, suggesting a need to develop persuasion strategies to motivate such behaviors. Therefore, with an experiment of 256 participants recruited from Amazon MTurk, this study examines how effectively norm-based messages improve positive behavioral intentions during the COVID-19 pandemic. Findings suggest that among individuals with high perceived severity of misinformation, exposure to both descriptive and injunctive norms about verification reduced their intention to rectify misinformation. However, both descriptive and injunctive norms about debunking misinformation increased intentions to engage in preventive behaviors. By probing the “self–other” discrepancy and the “trade-off effect” of risk appraisal, the study further reveals that the perceived severity of misinformation merits in-depth exploration in future research.

Analyzing COVID-19 disinformation on Twitter using the hashtags #scamdemic and #plandemic: Retrospective study.

The use of social media during the COVID-19 pandemic has led to an "infodemic" of mis- and disinformation with potentially grave consequences. To explore means of counteracting disinformation, we analyzed tweets containing the hashtags #Scamdemic and #Plandemic. Using a Twitter scraping tool called twint, we collected 419,269 English-language tweets that contained "#Scamdemic" or "#Plandemic" posted in 2020. Using the Twitter application-programming interface, we extracted the same tweets (by tweet ID) with additional user metadata. We explored descriptive statistics of tweets including their content and user profiles, analyzed sentiments and emotions, performed topic modeling, and determined tweet availability in both datasets. After removal of retweets, replies, non-English tweets, or duplicate tweets, 40,081 users tweeted 227,067 times using our selected hashtags. The mean weekly sentiment was overall negative for both hashtags. One in five users who used these hashtags were suspended by Twitter by January 2021. Suspended accounts had an average of 610 followers and an average of 6.7 tweets per user, while active users had an average of 472 followers and an average of 5.4 tweets per user. The most frequent tweet topic was "Complaints against mandates introduced during the pandemic" (79,670 tweets), which included complaints against masks, social distancing, and closures. While social media has democratized speech, it also permits users to disseminate potentially unverified or misleading information that endangers people's lives and public health interventions. Characterizing tweets and users that use hashtags associated with COVID-19 pandemic denial allowed us to understand the extent of misinformation. With the preponderance of inaccessible original tweets, we concluded that posters were in denial of the COVID-19 pandemic and sought to disperse related mis- or disinformation resulting in suspension. Leveraging 227,067 tweets with the hashtags #scamdemic and #plandemic in 2020, we were able to elucidate important trends in public disinformation about the COVID-19 vaccine.

Understanding How and by Whom COVID-19 Misinformation is Spread on Social Media: Coding and Network Analyses.

BackgroundDuring global health crises such as the COVID-19 pandemic, rapid spread of misinformation on social media has occurred. The misinformation associated with COVID-19 has been analyzed, but little attention has been paid to developing a comprehensive analytical framework to study its spread on social media.ObjectiveWe propose an elaboration likelihood model–based theoretical model to understand the persuasion process of COVID-19–related misinformation on social media.MethodsThe proposed model incorporates the central route feature (content feature) and peripheral features (including creator authority, social proof, and emotion). The central-level COVID-19–related misinformation feature includes five topics: medical information, social issues and people’s livelihoods, government response, epidemic spread, and international issues. First, we created a data set of COVID-19 pandemic–related misinformation based on fact-checking sources and a data set of posts that contained this misinformation on real-world social media. Based on the collected posts, we analyzed the dissemination patterns.ResultsOur data set included 11,450 misinformation posts, with medical misinformation as the largest category (n=5359, 46.80%). Moreover, the results suggest that both the least (4660/11,301, 41.24%) and most (2320/11,301, 20.53%) active users are prone to sharing misinformation. Further, posts related to international topics that have the greatest chance of producing a profound and lasting impact on social media exhibited the highest distribution depth (maximum depth=14) and width (maximum width=2355). Additionally, 97.00% (2364/2437) of the spread was characterized by radiation dissemination.ConclusionsOur proposed model and findings could help to combat the spread of misinformation by detecting suspicious users and identifying propagation characteristics.

COVID-19 information-seeking behaviors and preventive behaviors among college students in Oklahoma

Objective: To explore experiences, beliefs, and information-seeking behavior around COVID-19 among college students in Oklahoma. Participants: Fifteen college students participated during the pandemic period from April to July 2020. Methods: An exploratory, qualitative research approach method was used to discover students’ experiences, beliefs, and information-seeking behaviors around COVID-19. Exploration of beliefs was guided by the Health Belief Model. Results: Students engaged in COVID-19 information-seeking behaviors predominantly through Internet sites, broadcast news, health professionals, and governmental sources. Students experienced emotional burden as a result of COVID-19 misinformation in these sources. While most students perceived a low chance of acquiring the virus due to their lack of underlying medical conditions, they were still concerned about the consequences of becoming infected. Students noted the difficulty of physical distancing while on campus. Conclusions: Colleges/universities should maximize the dissemination of timely, valid health information for the safety of their students and the broader community.

Sentinel node approach to monitoring online COVID-19 misinformation

Understanding how different online communities engage with COVID-19 misinformation is critical for public health response. For example, misinformation confined to a small, isolated community of users poses a different public health risk than misinformation being consumed by a large population spanning many diverse communities. Here we take a longitudinal approach that leverages tools from network science to study COVID-19 misinformation on Twitter. Our approach provides a means to examine the breadth of misinformation engagement using modest data needs and computational resources. We identify a subset of accounts from different Twitter communities discussing COVID-19, and follow these ‘sentinel nodes’ longitudinally from July 2020 to January 2021. We characterize sentinel nodes in terms of a linked domain preference score, and use a standardized similarity score to examine alignment of tweets within and between communities. We find that media preference is strongly correlated with the amount of misinformation propagated by sentinel nodes. Engagement with sensationalist misinformation topics is largely confined to a cluster of sentinel nodes that includes influential conspiracy theorist accounts. By contrast, misinformation relating to COVID-19 severity generated widespread engagement across multiple communities. Our findings indicate that misinformation downplaying COVID-19 severity is of particular concern for public health response. We conclude that the sentinel node approach can be an effective way to assess breadth and depth of online misinformation penetration.

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.

Infodemi COVID-19 dengan Peran Social Media Fatigue, Deficient Self-Regulation, dan Promosi Diri

Social media envelopes a tremendous impact on the spread of the COVID-19 virus information. Nevertheless, this also increases the probability of misinformation-spreading as well. Using the affordace theory as well as the cognitive load theory, this study aims to analyze the effects of social media fatigue (SMF), deficient self-regulation (DS-R), and self-promotion on the spread of the COVID-19 misinformation on social media. The population of this research includes Indonesian social media users in the age range of 18 to 24 years old, with a number of sample N=155 (retrieved from G*power software). We use the Likert scale for our questionnaire, and the convenience sampling method for our study, spreading the questionnaire through online platforms such as LINE, WhatsApp, and Instagram. The data will then be analyzed using the SPSS software. Keywords: misinformation, social media, COVID-19

Characterizing User Susceptibility to COVID-19 Misinformation on Twitter

Though significant efforts such as removing false claims and promoting reliable sources have been increased to combat COVID-19 misinfodemic, it remains an unsolved societal challenge if lacking a proper understanding of susceptible online users, i.e., those who are likely to be attracted by, believe and spread misinformation. This study attempts to answer who constitutes the population vulnerable to the online misinformation in the pandemic, and what are the robust features and short-term behavior signals that distinguish susceptible users from others. Using a 6-month longitudinal user panel on Twitter collected from a geopolitically diverse network-stratified samples in the US, we distinguish different types of users, ranging from social bots to humans with various level of engagement with COVID-related misinformation. We then identify users' online features and situational predictors that correlate with their susceptibility to COVID-19 misinformation. This work brings unique contributions: First, contrary to the prior studies on bot influence, our analysis shows that social bots' contribution to misinformation sharing was surprisingly low, and human-like users' misinformation behaviors exhibit heterogeneity and temporal variability. While the sharing of misinformation was highly concentrated, the risk of occasionally sharing misinformation for average users remained alarmingly high. Second, our findings highlight the political sensitivity activeness and responsiveness to emotionally-charged content among susceptible users. Third, we demonstrate a feasible solution to efficiently predict users' transient susceptibility solely based on their short-term news consumption and exposure from their networks. Our work has an implication in designing effective intervention mechanism to mitigate the misinformation dissipation.

Drink Bleach or Do What Now? COVID-HeRA: A Study of Risk-Informed Health Decision Making in the Presence of COVID-19 Misinformation

Given the widespread dissemination of inaccurate medical advice related to the 2019 coronavirus pandemic (COVID-19), such as fake remedies, treatments and prevention suggestions, misinformation detection has emerged as an open problem of high importance and interest for the research community. Several works study health misinformation detection, yet little attention has been given to the perceived severity of misinformation posts. In this work, we frame health misinformation as a risk assessment task. More specifically, we study the severity of each misinformation story and how readers perceive this severity, i.e., how harmful a message believed by the audience can be and what type of signals can be used to recognize potentially malicious fake news and detect refuted claims. To address our research questions, we introduce a new benchmark dataset, accompanied with detailed data analysis. We evaluate several traditional and state-of-the-art models, and show there is a significant gap in performance when applying traditional misinformation classification models to this task. We conclude with open challenges and future directions.