ArticleComputers in human behavior2022
Factors influencing fake news rebuttal acceptance during the COVID-19 pandemic and the moderating effect of cognitive ability.
Article in Computers in human behavior, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Does fact-checking COVID-19 fake news on social media correct readers' false beliefs? A study of Chinese youths.Frontiers in psychology · 2026Article
- Influence of Information Sources and Group Norms on University Students' Online Rumor Refuting Behavior During Public Health Emergencies.Behavioral sciences (Basel, Switzerland) · 2025Article
- Understanding how users identify health misinformation in short videos: an integrated analysis using PLS-SEM and fsQCA.Frontiers in public health · 2025Article
- The spread of fake news: Disclosure willingness role.Heliyon · 2024Article
- News Coverage of the COVID-19 Pandemic on Social Media and the Public's Negative Emotions: Computational Study.Journal of medical Internet research · 2024Article
- Factors influencing public participation behavior relating to government microblogs on COVID-19 updates.Frontiers in public health · 2024Article
- Online rumors during the COVID-19 pandemic: co-evolution of themes and emotions.Frontiers in public health · 2024Article
- Readable and neutral? Reliability of crowdsourced misinformation debunking through linguistic and psycholinguistic cues.Frontiers in psychology · 2024Article
- Factors influencing college students' online rumor refuting behavior during major public health crises: the moderating effect of group norms.Frontiers in psychology · 2024Article
- Exploring rumor behavior during the COVID-19 pandemic through an information processing perspective: The moderating role of critical thinking.Computers in human behavior · 2023Article
- Infodemic: Challenges and solutions in topic discovery and data process.Archives of public health = Archives belges de sante publique · 2023Article
- Digital and physical factors influencing an individual's preventive behavior during the COVID-19 pandemic in Taiwan: A perspective based on the S-O-R model.Computers in human behavior · 2023Article
- Extracting Useful Emergency Information from Social Media: A Method Integrating Machine Learning and Rule-Based Classification.International journal of environmental research and public health · 2023Article
- Social Media News Use and COVID-19 Misinformation Engagement: Survey Study.Journal of medical Internet research · 2022Article
- Article
- A systematic literature review and existing challenges toward fake news detection models.Social network analysis and mining · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fake news is spreading rapidly on social media and poses a serious threat to the COVID-19 outbreak response. This study thus aims to reveal the factors influencing the acceptance of fake news rebuttals on Sina Weibo. Drawing on the elaboration likelihood model (ELM), we used text mining and the econometrics method to investigate the relationships among the central route (rebuttal's information readability and argument quality), peripheral route (rebuttal's source credibility, including authority and influence), and rebuttal acceptance, as well as the moderating effect of receiver's cognitive ability on these relationships. Our findings suggest that source authority had a negative effect on rebuttal acceptance, while source influence had a positive effect. Second, both information readability and argument quality had positive effects on rebuttal acceptance. In addition, individuals with low cognitive abilities relied more on source credibility and argument quality to accept rebuttals, while individuals with high cognitive abilities relied more on information readability. This study can provide decision support for practitioners to establish more effective fake news rebuttal strategies; it is especially valuable to reduce the negative impact of fake news related to major public health emergencies and safeguard the implementation of anti-epidemic strategies.
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