Evidence map›Paper›PMID 36846271›Full record

ArticleComputers in human behavior2023

Dialogic communication on local government social media during the first wave of COVID-19: Evidence from the health commissions of prefecture-level cities in China.

Qiang Chen, Yangyi Zhang, Huan Liu, Wei Zhang, Richard Evans

Abstract read
In one paragraph

Article in Computers in human behavior, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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.

Qiang ChenSchool of Journalism and New Media, Xi'an Jiaotong University, Xi'an, China.
Yangyi ZhangSchool of Journalism and New Media, Xi'an Jiaotong University, Xi'an, China.
Huan LiuSchool of Journalism and New Media, Xi'an Jiaotong University, Xi'an, China.
Wei ZhangSchool of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan, China.
Richard EvansFaculty of Computer Science, Dalhousie University, Halifax, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although some scholars have explored the level and determinants of Dialogic Communication on Government Social Media (DCGSM), none have conducted their studies in the context of public crisis. The current study contributes to the understanding on DCGSM by 16,822 posts crawled from the official Sina Weibo accounts of 104 Chinese health commissions in prefecture-level cities during the first wave of the COVID-19 pandemic. Results show that Chinese local government agencies have great variations in their DCGSM during the pandemic and the overall performance is poor. Furthermore, Chinese local governments prefer to conserve visitors and generate return visits, rather than dialogic loops development and the usefulness of information enhancement. The findings suggest that both public pressure and peer pressure contribute to the DCGSM of Chinese local governments during the public health crisis. In addition, the effect of public pressure is stronger than that of the peer pressure, indicating that local government agencies have experienced more demand-pull DCGSM.

Indexed as

Dialogic communication theoryDialogic strategiesGovernment social mediaPeer pressurePublic health crisesPublic pressure

Identifiers

PMID36846271
PMCPMC9937550

What OpenQuestion holds

Textmetadata
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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 OpenQuestion graph.