Antecedents and Consequences of Misinformation Sharing Behavior among Adults on Social Media during Covid-19
Datos Bibliográficos
| ID | 4182001 |
|---|---|
| Autores | Ammara Malik (0000-0002-1190-7383, University of the Punjab), Faiza Bashir (0000-0002-1507-063X, Lahore College for Women University, autor de correspondencia), Khalid Mahmood (0000-0003-1601-7168, University of the Punjab) |
| Año | 2023 |
| Volumen | 13 |
| Número | 1 |
| Páginas | 21582440221147022-21582440221147022 |
| Fecha de publicación | 2023-01-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | SAGE Open (JOURNAL) |
| Identificadores de la revista | ISSN: 2158-2440 • E-ISSN: 2158-2440 |
| Editorial | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/21582440221147022 |
| PMID | 36699545 |
| OpenAlex | W4318167642 |
| Idioma | EN |
| Citas recibidas | 17 |
| Referencias citadas | 50 |
Misinformation has been existed for centuries, though emerge as a severe concern in the age of social media, and particularly during COVID-19 global pandemic. As the pandemic approached, a massive influx of mixed quality data appeared on social media, which had adverse effects on society. This study highlights the possible factors contributing to the sharing and spreading misinformation through social media during the crisis. Preferred Reporting Items and Meta-Analysis guidelines were used for systematic review. Anxiety or risk perception associated with COVID-19 was one of the significant motivators for misinformation sharing, followed by entertainment, information seeking, sociability, social tie strength, self-promotion, trust in science, self-efficacy, and altruism. WhatsApp and Facebook were the most used platforms for spreading rumors and misinformation. The results indicated five significant factors associated with COVID-19 misinformation sharing on social media, including socio-demographic characteristics, financial considerations, political affiliation or interest, conspiracy ideation, and religious factors. Misinformation sharing could have profound consequences for individual and society and impeding the efforts of government and health institutions to manage the crisis. This SLR focuses solely on quantitative studies, hence, studies are overlooked from a qualitative standpoint. Furthermore, this study only looked at the predictors of misinformation sharing behavior during COVID-19. It did not look into the factors that could curb the sharing of misinformation on social media platforms as a whole. The study's findings will help the public, in general, to be cautious about sharing misinformation, and the health care workers, and institutions, in particular, for devising strategies and measures to reduce the flow of misinformation by releasing credible information through concerned official social media accounts. The findings will be valuable for health professionals and government agencies to devise strategies for handling misinformation during public health emergencies
Misinformation · Political science · Public relations · Social media · Misinformation and Its Impacts · Psychology · Public Relations and Crisis Communication · Social Media and Politics · Social Psychology
Pandemic Pregnancy Experiences and Risk Mitigation Behaviors
Integrating Social Explanations Into Explainable Artificial Intelligence (XAI) for Combating Misinformation
Drivers of vaccine mis/disinformation in the media
Susceptibility to digital health misinformation
Understanding Social Media Behaviour
Perceived Classroom Practices, Critical Thinking, and Fake-News Detection and Sharing
Prebunking false information in the wild
Wellness Misinformation on Social Media
Exploring Gender-Specific Nuances in Social Media Health Information Sharing
Joint Effect of Accuracy Nudge and Warning Label Interventions on Intention to Share Covid-19 Misinformation
Using social media for e-government services in Pakistan
Users' unverified information-sharing behavior on social media
Post-truth politics vs. newspaper coverage
The Dynamics of Misinformation Sharing
Media Trust and Misinformation
What Makes Fake News Appeal to You? Empirical Evidence from the Tweets Related to Covid-19 Vaccines
Who Is Spreading AI-Generated Health Rumors? A Study on the Association Between Aigc Interaction Types and the Willingness to Share Health Rumors
Social Media Use and Mental Health during the Covid‐19 Pandemic
Beliefs in Conspiracy Theories and Misinformation About Covid-19
Misinformation About Covid-19 Vaccines on Social Media
Sharing of fake news on social media
Trends and Predictors of Covid-19 Information Sources and Their Relationship With Knowledge and Beliefs Related to the Pandemic
Covid-19 Misinformation Online and Health Literacy
Towards a Methodology for Developing Evidence‐Informed Management Knowledge by Means of Systematic Review
The PRISMA 2020 statement
How shades of truth and age affect responses to Covid-19 (Mis)information
Retracted
It doesn’t take a village to fall for misinformation
Understanding the Facebook Users' Behavior towards Covid-19 Information Sharing by Integrating the Theory of Planned Behavior and Gratifications
Fake news and Covid-19
Seeking Formula for Misinformation Treatment in Public Health Crises
Effects of misinformation on Covid-19 individual responses and recommendations for resilience of disastrous consequences of misinformation
Misinformation sharing and social media fatigue during Covid-19
Fighting Covid-19 Misinformation on Social Media
The psychological effects of the Covid-19 pandemic and coping with them in Saudi Arabia
Facing Loneliness and Anxiety During the Covid-19 Isolation
Infodemic and Fake News in Spain during the Covid-19 Pandemic
Misinformation about Covid-19
Believing and sharing misinformation, fact-checks, and accurate information on social media
What to Believe? Social Media Commentary and Belief in Misinformation
When Corrections Fail
| Obras citantes distintas | 17 |
|---|---|
| Citas por año | 8,5 |
| Intervalo de citas | 2024 - 2026 (3) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 17 |