Evidence map›Paper›PMID 37809491›Full record

ArticleHeliyon2023

Spatiotemporal pattern evolution and influencing factors of online public opinion--Evidence from the early-stage of COVID-19 in China.

Jing Wang, Xukun Zhang, Wubin Liu, Pei Li

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. 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

4 authors.

Jing WangSchool of Economics and Management, Fuzhou University, Fuzhou, 350116, China.
Xukun ZhangSchool of Economics and Management, Fuzhou University, Fuzhou, 350116, China.
Wubin LiuSchool of Economics and Management, Fuzhou University, Fuzhou, 350116, China.
Pei LiSchool of Economics and Management, Fuzhou University, Fuzhou, 350116, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid development of internet information technology, online public opinion's influence is infinitely magnified, seriously threatening social security and national governance. It is significant to clarify the spatial and temporal evolution rules of online public opinion on major epidemics and its influencing factors for the governance and guidance of online public opinion on major epidemics. In this paper, the spatiotemporal evolution analysis model of online public opinion and an analysis model of influencing factors were constructed. We selected the Baidu index and microblog crawler text data at the early stage of COVID-19 as the research objects and analyzed the evolution of online public opinion during the time period by using the optimal segmentation method, spatial autocorrelation analysis, and text analysis method. The spatiotemporal evolutionary influences and their influence are further analyzed using the geographic probe factor detection method. The results showed that the evolution of online public opinion in the early stage of the epidemic was closely related to the event's evolution and the prevention and control effect. In the time dimension, the early evolution of online public opinion has prominent periodic characteristics. In the geospatial dimension, there are significant spatial agglomeration effects and spillover effects. In the cyberspace dimension, there are significant differences in online public opinion heat, hot topics, and netizens' emotional tendencies at different stages. Furthermore, the severity of the epidemic, the number of Internet users, the number of media reports and the region's attributes jointly affect the spatial and temporal evolution pattern of online public opinions about the epidemic. The research results provide decision-making references for the government and planners to effectively manage online public opinion on emergencies and improve the government's public opinion governance capacity and level.

Indexed as

COVID-19 pandemicInfluencing factorsOnline public opinionPublic opinion governanceSpatiotemporal pattern evolution

Identifiers

PMID37809491
PMCPMC10559807

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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 OpenQuestion graph.