ArticleFrontiers in public health2021
Online Rumor Diffusion Model Based on Variation and Silence Phenomenon in the Context of COVID-19.
Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 23 citations in OpenAlex.
- Identifying Network Propagation Sources Using Advanced Centrality Measures.Entropy (Basel, Switzerland) · 2025Article
- Detecting rumor outbreaks in online social networks.Social network analysis and mining · 2023Article
- Dynamic analysis and optimal control considering cross transmission and variation of information.Scientific reports · 2022Article
- A Novel Credible Carbon Footprint Traceability System for Low Carbon Economy Using Blockchain Technology.International journal of environmental research and public health · 2022Article
- Exploring an Efficient Evolutionary Game Model for the Government-Enterprise-Public during the Double Carbon Policy in China.International journal of environmental research and public health · 2022Article
- Exploring a Multi-Layer Coupled Network Propagation Model Based on Information Diffusion and Bounded Trust.International journal of public health · 2022Article
- Social Relationship Prediction Integrating Personality Traits and Asymmetric Interactions.Frontiers in psychology · 2022Article
- Visualization and Bibliometric Analysis of Carbon Neutrality Research for Global Health.Frontiers in public health · 2022Article
- Research on the dissemination of celebrities' opinions based on speech act theory and potential category analysis.Frontiers in psychology · 2022Article
- Sharing Reward Program Based on Face Consciousness in Social Media.Psychology research and behavior management · 2022Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the era of mobile internet, information dissemination has made a new leap in speed and in breadth. With the outbreak of the coronavirus disease 2019 (COVID-19), the COVID-19 rumor diffusion that is not limited by time and by space often becomes extremely complex and fickle. It is also normal that a piece of unsubstantiated news about COVID-19 could develop to many versions. We focus on the stagnant role and information variants in the process of rumor diffusion about COVID-19, and through the study of variability and silence in the dissemination, which combines the effects of stagnation phenomenon and information variation on the whole communication system in the circulation of rumors about COVID-19, based on the classic rumor SIR (Susceptible Infected Recovered) model, we introduce a new concept of "variation" and "oyster". The stability of the new model is analyzed by the mean field equation, and the threshold of COVID-19 rumor propagation is obtained later. According to the results of the simulation experiment, whether in the small world network or in the scale-free network, the increase of the immure and the silent probability of the variation can effectively reduce the speed of rumor diffusion about COVID-19 and is conducive to the dissemination of the truth in the whole population. Studies have also shown that increasing the silence rate of variation can reduce COVID-19 rumor transmission more quickly than the immunization rate. The interesting discovery is that at the same time, a higher rumor infection rate can bring more rumors about COVID-19 but does not always maintain a high number of the variation which could reduce variant tendency of rumors. The more information diffuses in the social group, the more consistent the version and content of the information will be, which proves that the more adequate each individual information is, the slower and less likely rumors about COVID-19 spread. This consequence tells us that the government needs to guide the public to the truth. Announcing the true information publicly could instantly contain the COVID-19 rumor diffusion well rather than making them hidden or voiceless.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.