Evidence map›Paper›PMID 35155348›Full record

ArticleFrontiers in public health2021

Online Rumor Diffusion Model Based on Variation and Silence Phenomenon in the Context of COVID-19.

Chunhua Ju, Yihao Jiang, Fuguang Bao, Bilin Zou, Chonghuan Xu

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
8.7field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Detecting rumor outbreaks in online social networks.Social network analysis and mining · 2023
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  4. A Novel Credible Carbon Footprint Traceability System for Low Carbon Economy Using Blockchain Technology.International journal of environmental research and public health · 2022
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  10. Sharing Reward Program Based on Face Consciousness in Social Media.Psychology research and behavior management · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Chunhua JuModern Business Research Center, Zhejiang Gongshang University, Hangzhou, China.
Yihao JiangSchool of Management Science and Engineering, Zhejiang Gongshang University, Hangzhou, China.
Fuguang BaoModern Business Research Center, Zhejiang Gongshang University, Hangzhou, China.
Bilin ZouSchool of Management Science and Engineering, Zhejiang Gongshang University, Hangzhou, China.
Chonghuan XuAcademy of Zhejiang Culture Industry Innovation and Development, Zhejiang Gongshang University, Hangzhou, China.
Zhejiang Gongshang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

COVID-19Social MediaDisease OutbreaksHumansInformation DisseminationSARS-CoV-2COVID-19 rumor diffusioninfection rateISVOR modeloystervariation

Identifiers

PMID35155348
PMCPMC8829072
OpenAlexW4210780154

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.