Evidence map›Paper›PMID 36268221›Full record

ArticleComputers in human behavior2023

Fighting rumors to fight COVID-19: Investigating rumor belief and sharing on social media during the pandemic.

Feng Guo, Apan Zhou, Xiaofei Zhang, Xinxiang Xu, Xuekun Liu

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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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.

Feng GuoCollege of Management and Economics, Tianjin University, Tianjin, China.
Apan ZhouCollege of Management and Economics, Tianjin University, Tianjin, China.
Xiaofei ZhangBusiness School, Nankai University, Tianjin, China.
Xinxiang XuBusiness School, Nankai University, Tianjin, China.
Xuekun LiuBusiness School, Nankai University, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The outbreak of the coronavirus disease (COVID-19) pandemic, a significant health threat, influenced information-related behaviors and induced increased rumor-sharing behaviors on social media. Fighting COVID-19 thus entails the need to fight the rumors as well, providing a strong motivation to explore rumor-related behavior during this extraordinary period. From the perspective of information acquisition, we predicted that information acquisition from social and traditional media would interactively influence rumor-related decisions (i.e., rumor belief and sharing) and that critical thinking would shape this relationship. Through a survey of 2424 individuals who used social media during the pandemic, we found that information acquisition from social media was negatively related to rumor sharing and that rumor belief mediated this relationship. Meanwhile, information acquisition from traditional media weakened the negative effect of information acquisition from social media on rumor belief, and critical thinking alleviated the positive effect of rumor belief on rumor sharing. This study contributes to the literature by explaining the diffusion of COVID-19 rumors on social media from an information perspective and revealing how different information sources and thinking styles come into conflict in rumor decisions.

Indexed as

COVID-19 rumorCritical thinkingRumor beliefRumor sharingSocial mediaTraditional media

Identifiers

PMID36268221
PMCPMC9556004

What OpenQuestion holds

Textmetadata
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.