Evidence map›Paper›PMID 35052242›Full record

ArticleHealthcare (Basel, Switzerland)2021

The Relationship between Government Information Supply and Public Information Demand in the Early Stage of COVID-19 in China-An Empirical Analysis.

Tong Zhang, Li Yu

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Planning and Implementing Social Media Communication in a Public Health Crisis: An Analytical Perspective.Health promotion journal of Australia : official journal of Australian Association of Health Promotion Professionals · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

2 authors.

Tong ZhangSchool of Public Affairs, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0001-6039-2446
Li YuSchool of Public Affairs, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0001-9258-5963

Funding

China Postdoctoral Science Foundation 2021M692769Ministry of Education 18YJC870022 (Youth Foundation Project of Humanities and Social Sciences)Ministry of Education 21YJCZH207(Youth Foundation Project of Humanities and Social Sciences)
6 · The paper itself

Abstract

Accurate and effective government communication is essential for public health emergencies. To optimize the effectiveness of government crisis communication, this paper puts forward an analytical perspective of supply-demand matching based on the interaction between the government and the public. We investigate the stage characteristics and the topic evolutions of both government information supply and public information demand through combined statistical analysis, text mining, text coding and cluster analysis, using empirical data from the National Health Commission's WeChat in China. A quantitative measure reflecting the public demand for government information supply is proposed. Result indicates that the government has provided a large amount of high-intensity epidemic-related information, with six major topics being the medical team, government actions, scientific protection knowledge, epidemic situation, high-level deployment and global cooperation. The public's greatest information needs present different characteristics at different stages, with "scientific protection knowledge", "government actions" and "medical teams" being the most needed in the outbreak stage, the control stage and the stable stage, respectively. The subject of oversupply is "medical team", and the subject of short supply is "epidemic dynamics" and "science knowledge". This paper provides important theoretical and practical value for improving the effectiveness of government communication in public health crises.

Indexed as

COVID-19crisis communicationgovernment communicationgovernment social mediapublic health emergencysupply–demand matching

Identifiers

PMID35052242
PMCPMC8775904

What OpenQuestion 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 OpenQuestion graph.