Evidence map›Paper›PMID 41086434›Full record

ArticleJMIR medical informatics2025

Bibliometric Insights Into the Infodemic: Global Research Trends and Policy Responses: Quantitative Research.

Sijia Wang, Linan Zhang, Yang Liu, Xin Feng, Shipeng Ren

Abstract read
In one paragraph

Article in JMIR medical informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Sijia WangDepartment of Urban Construction, Hebei Normal University of Science and Technology, Qinhuangdao, China.ORCID 0009-0003-1189-8071
Linan ZhangSchool of Marxism, Shijiazhuang Tiedao University, Shijiazhuang, China.ORCID 0009-0009-8976-2784
Yang LiuSchool of Arts and Communication, Hebei University of Engincering Science, No.11, Gongbei Road, Qiaoxi District, Shijiazhuang, Hebei, 050018, China, 86 17732192671.ORCID 0009-0002-3162-2841
Xin FengThe Institute for Social and Cultural Research, Macau University of Science and Technology, Macau, China.ORCID 0000-0002-0140-8003
Shipeng RenSchool of Economics and Finance, Xi'an Jiaotong University, Xi'an, China.ORCID 0009-0006-6953-6323

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Amidst the COVID-19 pandemic, the proliferation of misinformation on social media, termed the "infodemic," has complicated global health responses. Objective: This study aims to identify research trends and information-making in the context of this challenge. This paper synthesizes key areas of scholarly investigation into the COVID-19 infodemic, both within China and internationally, to guide public health strategies and the management of public sentiment. Methods: By employing a bibliometric approach, using CiteSpace software, we conducted a visual analysis of the global literature, covering a total of 1437 publications from the Web of Science and the China National Knowledge Infrastructure core databases between 2016 and 2025, focusing on publication trends, citation frequencies, and keyword clusters. Results: After analysis, the results reveal distinct focal points in the research priorities of Chinese and international scholars. International studies often focus on machine learning and public psychology, while Chinese research tends to address information control and safeguarding. Common ground is found in the interest in preventing the spread of misinformation. While literature on COVID-19 abounds, cross-national systematic reviews are limited. Conclusions: This paper fills this gap through a comparative bibliometric analysis, offering valuable insights for information management, media communication, and public administration, thus charting new directions for future research.

Indexed as

BibliometricsCOVID-19Social MediaChinaGlobal HealthHumansPandemicsSARS-CoV-2bibliometricsinfodemicinformation governanceinformation spreadingsocial mediavisualization

Identifiers

PMID41086434
PMCPMC12520647

What OpenQuestion holds

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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.