Evidence map›Paper›PMID 39502228›Full record

ArticleHeliyon2024

Information spread behavior of clubhouse: A value-attitude-behavior model perspective.

Yu-Feng Wu, Yu-Tai Wu, Jian-Hong Ye, Jhen-Ni Ye

Abstract read
In one paragraph

Article in Heliyon, 2024. 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

4 authors.

Yu-Feng WuOffice of Physical Education, Ming Chi University of Technology, New Taipei City, Taiwan.
Yu-Tai WuOffice of Physical Education, Soochow University, Taipei, Taiwan.
Jian-Hong YeFaculty of Education, Beijing Normal University, Beijing, China.
Jhen-Ni YeGraduate Institute of Technological & Vocational Education, National Taipei University of Technology, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prevalence of social media has significantly facilitated the spread and diffusion of online memes. The Clubhouse voice community application, which gained popularity rapidly during the COVID-19 pandemic and became widely used, can be regarded as a form of internet meme. However, the underlying reasons for this phenomenon have been scarcely explored. In this context, the purpose of this study is to understand the dissemination mechanisms of the Clubhouse voice community. Specifically, this research employs the value-attitude-behavior model to investigate the relationships between social value, attitude, immediate response syndrome, and information spread behavior on Clubhouse. To achieve this objective, the snowball sampling technique was used to recruit Clubhouse users to complete a questionnaire. The collected data were assessed for reliability and validity before being analyzed using structural equation modeling for confirmatory factor analysis and model verification. The results indicated that the social value of joining Clubhouse is positively associated with participants' attitudes toward participation. Additionally, attitudes toward participation were found to be positively associated with both immediate response syndrome and information spread behavior, thus showing a positive association between immediate response syndrome and information spread behavior. This study reveals the pathways of internet meme dissemination, offering insights into the factors driving the formation of internet memes.

Indexed as

Immediate response syndromeInformation spread behaviorInternet meme (网络迷因)Social valueValue-attitude-behavior modelVoice social media

Identifiers

PMID39502228
PMCPMC11535969

What OpenQuestion holds

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LicenceCC BY
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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.