Misinformation In Social Media Research Articles

Misinformation and work-related outcomes of healthcare community: Sequential mediation role of COVID-19 threat and psychological distress.

By applying coping theory, this study develops and tests a process model investigating the sequential mediating roles of perceived COVID‐19 threat and psychological distress on the relationships between social media misinformation and turnover intentions, and in‐role performance. Hypothesized model for Study 1 was fully supported, showing that the association between social media misinformation and turnover intentions are each mediated sequentially, first by perceived COVID‐19 threat and then by psychological distress. Additional support was found for the sequential mediation model when predicting turnover intentions and in‐role performance in Study 2, using time‐lagged data. Besides, this study found that resilience moderated social media misinformation's sequential indirect effect on turnover intentions and in‐role performance. Implications and future research directions have been discussed.

Exploring pharmacist experience and acceptance for debunking health misinformation in the social media


 Introduction: The increasing evidence of misinformation on pharmacy issues in Social Media (SM) may provide potential for pharmacist involvement. 
 Aim: This study aims at exploring pharmacist experience and acceptance to debunk pharmacy misinformation in SM. 
 Methods: Four Focus Group Discussions (FGDs) with 41 selected pharmacists were conducted. The FGDs collected participant’s experience with misinformation, action taken and participant’s acceptance for debunking misinformation. The FGDs were audio recorded, subsequently transcribed and thematically analysed. 
 Results: The majority of respondents often clarified the misinformation. Pharmacist motivation, relationship with the sender, opportunities to response and ability to respond the misleading message are themes determining pharmacist acceptance for debunking misinformation in SM.
 Conclusion: Pharmacist has the potential to contain and prevent misinformation about health and pharmacy issues in SM.

The Effect of a Wordless, Animated, Social Media Video Intervention on COVID-19 Prevention: Online Randomized Controlled Trial.

BackgroundInnovative approaches to the dissemination of evidence-based COVID-19 health messages are urgently needed to counter social media misinformation about the pandemic. To this end, we designed a short, wordless, animated global health communication video (the CoVideo), which was rapidly distributed through social media channels to an international audience.ObjectiveThe objectives of this study were to (1) establish the CoVideo’s effectiveness in improving COVID-19 prevention knowledge, and (2) establish the CoVideo’s effectiveness in increasing behavioral intent toward COVID-19 prevention.MethodsIn May and June 2020, we enrolled 15,163 online participants from the United States, Mexico, the United Kingdom, Germany, and Spain. We randomized participants to (1) the CoVideo arm, (2) an attention placebo control (APC) arm, and (3) a do-nothing arm, and presented 18 knowledge questions about preventive COVID-19 behaviors, which was our first primary endpoint. To measure behavioral intent, our second primary endpoint, we randomized participants in each arm to five list experiments.ResultsGlobally, the video intervention was viewed 1.2 million times within the first 10 days of its release and more than 15 million times within the first 4 months. Knowledge in the CoVideo arm was significantly higher (mean 16.95, 95% CI 16.91-16.99) than in the do-nothing (mean 16.86, 95% CI 16.83-16.90; P<.001) arm. We observed high baseline levels of behavioral intent to perform many of the preventive behaviors featured in the video intervention. We were only able to detect a statistically significant impact of the CoVideo on one of the five preventive behaviors.ConclusionsDespite high baseline levels, the intervention was effective at boosting knowledge of COVID-19 prevention. We were only able to capture a measurable change in behavioral intent toward one of the five COVID-19 preventive behaviors examined in this study. The global reach of this health communication intervention and the high voluntary engagement of trial participants highlight several innovative features that could inform the design and dissemination of public health messages. Short, wordless, animated videos, distributed by health authorities via social media, may be an effective pathway for rapid global health communication during health crises.Trial RegistrationGerman Clinical Trials Register DRKS00021582; https://tinyurl.com/6r4zkbbnInternational Registered Report Identifier (IRRID)RR2-10.1186/s13063-020-04942-7

Linguistic characteristics and the dissemination of misinformation in social media: The moderating effect of information richness

In recent years, there has been a rise in incorrect information, or misinformation, being shared on social media. Such misinformation tends to be more eye-catching and misleading. Previous studies on detecting misinformation online have focused mainly on linguistic characteristics; however, the role of linguistic characteristics in misinformation dissemination has not yet been thoroughly researched. In this study, we propose a misinformation dissemination model that includes the direct effects of four novel linguistic characteristics on dissemination and the moderating effect of information richness. The model is tested by using 9,631 examples of misinformation collected from Sina-Weibo, the leading social media platform in China. The results indicate that compared with correct information, misinformation containing persuasive and uncertainty words is more likely to be disseminated than misinformation containing emotional and comparative words. Furthermore, in the case of information richness, the results indicate that when the misinformation includes images, the effects of persuasive, negative emotion, comparative, and uncertainty words are strengthened, while the inclusion of videos weakens the effects of the linguistic characteristics. Finally, the results of robustness check by using the Fakenewsnet data set are consistent with our hypothesis, indicating that the four linguistic characteristics proposed by this study are also suitable for the dissemination of misinformation in English. The robustness check further demonstrates our method with well generalization.

Persuasion strategies of misinformation-containing posts in the social media

Social media users were found to be persuaded by misinformation and contribute to the propagation of misinformation. It is important and urgent to understand the mechanisms behind the presentation and diffusion of misinformation-containing posts in social media. However, majority of previous studies on online misinformation focused on the non-content or surface-linguistic features, which omitted the intrinsically sociological and psychological features behind the presentation of online misinformation. Based on persuasion theories, this study characterizes the usage of persuasion strategies and its influence on the propagation of misinformation-containing posts in Sina Weibo, which can help us better understand the sociological and psychological mechanism behind the presentation and diffusion of online misinformation. The findings of this study indicate that the pathos strategies are the most common acts of persuasion in misinformation-containing posts in contrast to regular posts. In addition, the type of persuasion strategies used in the misinformation-containing posts correlate with the topics, expected actions and digital elements of the posts. Furthermore, we found statistically significant effects of persuasion strategieson users’ responses to misinformation-containing posts. The findings of this study imply a complex and context-dependent mechanism behind the misinformation presentation and propagation, which shed lights on the efforts for fighting misinformation in social media.

Misinformation on social networks during the novel coronavirus pandemic: a quali-quantitative case study of Brazil

BackgroundOne of the challenges posed by the novel coronavirus pandemic is the infodemic risk, that is, a huge amount of information being published on the topic, along with misinformation and rumours; with social media, this phenomenon is amplified, and it goes faster and further. Around 100 million people in Brazil (50% of the inhabitants) are users of social media networks – almost half of the country’s population. Most of the information on the Internet is unregulated, and its quality remains questionable.MethodsIn this study, we examine the main characteristics of misinformation published on the topic. We analysed 232 pieces of misinformation published by the Brazilian fact-checking service “Agência Lupa”. The following aspects of each news item were analysed: a) In what social media has it circulated?; b) What is the content classification, sentiment and type of misinformation?; d) Are there recurrent themes in the sample studied?ResultsMost were published on Facebook (76%), followed by WhatsApp, with 10% of total cases. Half of the stories (47%) are classified as “real-life”, that is, the focus is on everyday situations, or circumstances involving people. Regarding the type of misinformation, there is a preponderance of fabricated content, with 53% of total, followed by false context (34%) and misleading content (13%). Wrong information was mostly published in text format (47%). We found that 92.9% of misinformation classified as “fabricated content” are “health tips”, and 88.9% of “virtual scams” are also fabricated.ConclusionBrazilian media and science communicators must understand the main characteristics of misinformation in social media about COVID-19, so that they can develop attractive, up-to-date and evidence-based content that helps to increase health literacy and counteract the spread of false information.

Social Media Misinformation and Conspiracy Theories pose a Great Threat to Successful COVID‐19 Vaccination Among Adults ages 18‐23

There are two main paths to herd immunity for COVID‐19 — vaccines or natural infection. Vaccination for SARS‐CoV‐2 (the virus that causes COVID‐19) is the ideal approach to achieving herd immunity. However, reaching herd immunity through vaccination has several challenges such as certain groups’ objection to vaccines due to religious objections, fears regarding possible risks or skepticism about the benefits. This objection and skepticism is of great concern to the current COVID‐19 vaccination campaign. If the proportion of vaccinated people in a community falls below the herd immunity threshold, exposure to contagious SARS‐CoV‐2 could result in a new surge of of COVID‐19. This concern is further magnified by the recent CDC findings that people with no symptoms transmit more than half (59%) of all COVID‐19 cases. This number includes 35% of new cases from people who infect others prior to showing symptoms and 24% of new cases from people who never develop symptoms.The spread of misinformation and conspiracy theories regarding COVID‐19 vaccination poses a great threat to the vaccination campaign of young adults. In an effort to further understand this current social media misinformation narrative, we surveyed college students between the ages of 18‐23 and their willingness to take the vaccine. Our survey included “fact checking” pieces of social media misinformation and investigated whether adults in this age group have been influenced by widely circulated misinformation. Our survey also included questions to investigate the potential that a significant portion of people in this age group might completely oppose vaccinations. Our findings further support the need for efficacious therapeutics for natural viral infection as an alternative to vaccination. Providing the population with an assortment of therapeutic options will reduce death caused by natural viral infection as the U.S. and world population attempts to reach herd immunity.

Gr\xfcnde f\xfcr die Ablehnung beh\xf6rdlicher Empfehlungen und Ma\xdfnahmen zum Schutz vor SARS-CoV-2\xa0\u2013 eine qualitative Studie auf Basis von Beitr\xe4gen in sozialen Medien

ZusammenfassungHintergrundUm die Ausbreitung von SARS-CoV‑2 (schweres akutes Atemwegssyndrom-Coronavirus-Typ 2) zu verlangsamen, haben Bund und Bundesländer Schutzmaßnahmen ergriffen, die weitreichende Folgen für die Bevölkerung haben. Diese Maßnahmen umfassen u. a. die zeitweise Einschränkung des Betriebs von Freizeiteinrichtungen sowie Kontakt- und Reiseeinschränkungen. Die Maßnahmen rufen gemischte Reaktionen hervor, wobei Teile der Bevölkerung Empfehlungen und Vorgaben ignorieren.Ziel der ArbeitZiel der vorliegenden Studie ist es, auf Basis der Beiträge in sozialen Medien die Gründe für die Ablehnung von Schutzmaßnahmen zu untersuchen.Material und Methoden3 soziale Netzwerke (Facebook, Twitter und Youtube-Kommentare) wurden für den Zeitraum 02.03. bis 18.04.2020 systematisch hinsichtlich der Einstellungen zu Kontaktbeschränkungen und anderen Schutzmaßnahmen mittels qualitativer Dokumenten- und Inhaltsanalyse untersucht. Insgesamt wurden 119 Beiträge in die Analyse aufgenommen und interpretiert.Ergebnisse6 Hauptkategorien und 4 Unterkategorien wurden im Zusammenhang mit der Ablehnung der Schutzmaßnahmen identifiziert: Fehlinformationen der sozialen Medien (Verharmlosung und Zweifel an der Wirksamkeit), Misstrauen gegenüber den etablierten öffentlichen Medien, Wissensdefizite und Verunsicherung, Einschränkung der Grundrechte, die Rolle der Behörden (Bevölkerungskontrolle und mangelndes Vertrauen in das Robert Koch-Institut) sowie wirtschaftliche Auswirkungen der Pandemie.DiskussionFehlinformationen in sozialen Medien und Wissensdefizite können zu einer Unterschätzung der Pandemie beitragen. Zudem können wirtschaftliche Belastungen mit der Ablehnung von Schutzvorkehrungen einhergehen. Zur Erhöhung der Akzeptanz implementierter Schutzmaßnahmen stellen Gesundheitsaufklärung sowie transparente und evidenzbasierte Kommunikation relevante Determinanten dar.

Social media misinformation during the COVID-19 pandemic: Impacts on public mental health

Social Media Misinformation During the COVID-19 Pandemic: Impacts on Public Mental HealthIntroductionSome behavioral measures such as handwashing, masking or social distancing are among the most effective tools to combat COVID-19 pandemic.ObjectivesDescribe the extent to which major media outlets in the United States and Spain have tweeted about COVID-19 health related behaviors, and determine if differences exist between major media outlets in the two countries.MethodsWe analyzed contents posted on Twitter by 25 major media outlet’s (15 from USA and 10 from Spain) about COVID health related behaviors (HRB). News content were analyzed and classified as well as Twitter users’ reactions.ResultsMasking and quarantine were the HRB that generated most of the tweets. However, we found differences between media outlets in the two countries. Twitter user´s engaged more with tweets posted by USA media. Most of the tweets describing HRB from the general population were consistent with CDC/WHO guidelines.ConclusionsUnderstanding the public view of these HRB is necessary to design promotional strategies aimed at the appropriate population.DisclosureNo significant relationships.

Examining the Roles of Multi-Platform Social Media News Use, Engagement, and Connections with News Organizations and Journalists on News Literacy: A Comparison of Seven Democracies

The proliferation of misinformation in social media has raised concerns on the veracity of news that citizens consume. Recent scholarship has therefore emphasized the importance of news literacy as higher levels imply greater competence in navigating the streams of information in the social media space. Drawing from subsamples of respondents who use social media for news in seven democracies (UK, Germany, Denmark, Spain, Ireland, Norway, and the US, N = 6774), this comparative analysis examines the dynamics of social media news platform use that influence news literacy. After controlling for demographics, news interest and news use frequency, analyses show that social media news engagement and connections to news organizations and journalists exhibited both positive direct and indirect relationships with news literacy. Multi-platform use of social media for news was also related to engagement, but in five countries the relationship with news literacy was negative.

Detecting fake news on Facebook: The role of emotional intelligence.

The proliferation of fake news on social media is now a matter of considerable public and governmental concern. In 2016, the UK EU referendum and the US Presidential election were both marked by social media misinformation campaigns, which have subsequently reduced trust in democratic processes. More recently, during the COVID-19 pandemic, the acceptance of fake news has been shown to pose a threat to public health. Research on how to combat the false acceptance of fake news is still in its infancy. However, recent studies have started to focus on the psychological factors which might make some individuals less likely to fall for fake news. Here, we adopt that approach to assess whether individuals who show high levels of ‘emotional intelligence’ (EQ) are less likely to fall for fake news items. That is, are individuals who are better able to disregard the emotionally charged content of such items, better equipped to assess the veracity of the information. Using a sample of UK participants, an established measure of EQ and a novel fake news detection task, we report a significant positive relationship between individual differences in emotional intelligence and fake news detection ability. We also report a similar effect for higher levels of educational attainment, and we report some exploratory qualitative fake news judgement data. Our findings are discussed in terms of their applicability to practical short term (i.e. current Facebook user data) and medium term (i.e. emotional intelligence training) interventions which could enhance fake news detection.

Understanding GI Twitter and Its Major Contributors

Understanding GI Twitter and Its Major Contributors

A value-driven approach to addressing misinformation in social media

Misinformation in social media is an actual and contested policy problem given its outreach and the variety of stakeholders involved. In particular, increased social media use makes the spread of misinformation almost universal. Here we demonstrate a framework for evaluating tools for detecting misinformation using a preference elicitation approach, as well as an integrated decision analytic process for evaluating desirable features of systems for combatting misinformation. The framework was tested in three countries (Austria, Greece, and Sweden) with three groups of stakeholders (policymakers, journalists, and citizens). Multi-criteria decision analysis was the methodological basis for the research. The results showed that participants prioritised information regarding the actors behind the distribution of misinformation and tracing the life cycle of misinformative posts. Another important criterion was whether someone intended to delude others, which shows a preference for trust, accountability, and quality in, for instance, journalism. Also, how misinformation travels is important. However, all criteria that involved active contributions to dealing with misinformation were ranked low in importance, which shows that participants may not have felt personally involved enough in the subject or situation. The results also show differences in preferences for tools that are influenced by cultural background and that might be considered in the further development of tools.

Prevalence of Health Misinformation on Social Media: Systematic Review.

BackgroundAlthough at present there is broad agreement among researchers, health professionals, and policy makers on the need to control and combat health misinformation, the magnitude of this problem is still unknown. Consequently, it is fundamental to discover both the most prevalent health topics and the social media platforms from which these topics are initially framed and subsequently disseminated.ObjectiveThis systematic review aimed to identify the main health misinformation topics and their prevalence on different social media platforms, focusing on methodological quality and the diverse solutions that are being implemented to address this public health concern.MethodsWe searched PubMed, MEDLINE, Scopus, and Web of Science for articles published in English before March 2019, with a focus on the study of health misinformation in social media. We defined health misinformation as a health-related claim that is based on anecdotal evidence, false, or misleading owing to the lack of existing scientific knowledge. We included (1) articles that focused on health misinformation in social media, including those in which the authors discussed the consequences or purposes of health misinformation and (2) studies that described empirical findings regarding the measurement of health misinformation on these platforms.ResultsA total of 69 studies were identified as eligible, and they covered a wide range of health topics and social media platforms. The topics were articulated around the following six principal categories: vaccines (32%), drugs or smoking (22%), noncommunicable diseases (19%), pandemics (10%), eating disorders (9%), and medical treatments (7%). Studies were mainly based on the following five methodological approaches: social network analysis (28%), evaluating content (26%), evaluating quality (24%), content/text analysis (16%), and sentiment analysis (6%). Health misinformation was most prevalent in studies related to smoking products and drugs such as opioids and marijuana. Posts with misinformation reached 87% in some studies. Health misinformation about vaccines was also very common (43%), with the human papilloma virus vaccine being the most affected. Health misinformation related to diets or pro–eating disorder arguments were moderate in comparison to the aforementioned topics (36%). Studies focused on diseases (ie, noncommunicable diseases and pandemics) also reported moderate misinformation rates (40%), especially in the case of cancer. Finally, the lowest levels of health misinformation were related to medical treatments (30%).ConclusionsThe prevalence of health misinformation was the highest on Twitter and on issues related to smoking products and drugs. However, misinformation on major public health issues, such as vaccines and diseases, was also high. Our study offers a comprehensive characterization of the dominant health misinformation topics and a comprehensive description of their prevalence on different social media platforms, which can guide future studies and help in the development of evidence-based digital policy action plans.

Infodemiology: Computational Methodologies for Quantifying and Visualizing Key Characteristics of the COVID-19 Infodemic

Objectives. Infodemics of false information on social media is a growing societal problem, aggravated by the occurrence of the COVID-19 pandemic. The development of infodemics has characteristic resemblances to epidemics of infectious diseases. This paper presents several methodologies which aim to measure the extent and development of infodemics through the lens of epidemiology.Methods. Time varying R was used as a measure for the infectiousness of the infodemic, topic modeling was used to create topic clouds and topic similarity heat maps, while network analysis was used to create directed and undirected graphs to identify super-spreader and multiple carrier communities on social media. Results. Forty-two (42) latent topics were discovered. Reproductive trends for a specific topic were observed to have significantly higher peaks (Rt 4-5) than general misinformation (Rt 1-3). From a sample of social media misinformation posts, a total of 385 groups and 804 connections were found within the network, with the largest group having 1,643 shares and 1,063,579 interactions over a 12 month period.Conclusions. These approaches enable the measurement of the infectiousness of an infodemic, comparative analysis of infodemic topics, and identification of likely super-spreaders and multiple carriers on social media. The results of these analyses can form the basis for taking action to stem an ongoing spread of misinformation on social media and mitigate against future infodemics. The methods are not confined to health misinformation and may be applied to other infodemics, such as conspiracy theories, political disinformation, and climate change denial.

Embracing Social Media as a Modern Means of Health Promotion: Can We “Like” and “Share” Our Way Towards Better Population Health?

Over the past year, the world has been drastically impacted by the COVID-19 pandemic. While some sectors have successfully embraced the accelerated way in which societies were forced to digitize, it could be said that the public health sector has not fully taken advantage of the opportunities presented by social media. This article explores some of the benefits of using social media as a means of health communication, particularly with regards to faster dissemination of information and benefits to mental health during the COVID-19 pandemic. Concerns surrounding social media misinformation and the “digital divide” are also addressed and recommendations are made on how they can be tackled. Furthermore, real-life case studies from the Pacific Islands region and Finland are explored so as to identify ways in which similar frameworks and strategies can be applied in other similar communities across the world.

Pediatric Infectious Disease Specialists: An Answer to Social Media Misinformation on Coronavirus Disease 2019.

Pediatric Infectious Disease Specialists: An Answer to Social Media Misinformation on Coronavirus Disease 2019.

Social Media as Vehicle for Conspiracy Beliefs on COVID-19

Highlights:&#x0D; &#x0D; Conspiracy beliefs are spread via social media platforms and may have a negative impact on preventive health measures&#x0D; Preventive measures against fear and misinformation need to consider the differential effects of different forms of conspiracy theories on behavior&#x0D; Fostering awareness in society about COVID-19 misinformation in social media is crucial.&#x0D;

SOCIAL MEDIA AND FAKE NEWS ON CORONA VIRUS: A REVIEW OF LITERATURE

Social media is the 21st-century media that has given every user an equal opportunity to publish news without passing through any form of gatekeeping, editorial, or professional scrutiny. This means that it has become a natural home for the spread of fake news even on the recent coronavirus with its consequent health implications. The authors deployed available materials and literature to discuss the burning issues surrounding fake news as misleading information on social media, especially how social media has become a natural home for fake news on coronavirus. More so, this paper reviewed the literature on the effects of fake news on coronavirus and then motivations for sharing fake news online as a way to provide a start-off point for an understanding of why social media misinformation on Corona virus has spread. The authors concluded by presenting a gap in literature, in addition to a research agenda for studies on the spread of health-related disinformation in Nigeria.

Multitask deep learning for native language identification

Identifying the native language of a person by their text written in English (L1 identification) plays an important role in such tasks as authorship profiling and identification. With the current proliferation of misinformation in social media, these methods are especially topical. Most studies in this field have focused on the development of supervised classification algorithms, that are trained on a single L1 dataset. Although multiple labeled datasets are available for L1 identification, they contain texts authored by speakers of different languages and do not completely overlap. Current approaches achieve high accuracy on available datasets, but this is attained by training an individual classifier for each dataset. Studies show that joint training of multiple classifiers on different datasets can result in sharing information between the classifiers, leading to an increase in the accuracy of both tasks. In this study, we develop a novel deep neural network (DNN) architecture for L1 classification; it is based on an adversarial multitask learning method that integrates shared knowledge from multiple L1 datasets. We propose several variants of the architecture and rigorously evaluate their performance on multiple datasets. Our results indicate the proposed multitask architecture is more efficient in terms of classification accuracy than previously proposed methods.