Evidence map›Paper›PMID 38626024›Full record

ArticlePloS one2024

The projection of Chinese University online image and social media engagement based on Bayesian model.

Dongmei Xia, Pengfei Zhao, Ji Wang, Yingji Li

Abstract read
In one paragraph

Article in PloS one, 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.

Dongmei XiaSchool of Education Science, Xinjiang Normal University, Wulumuqi, China.
Pengfei ZhaoVocational Ability Development Research Center, Chongqing Institute of Engineering, Chongqing, China.
Ji WangVocational Ability Development Research Center, Chongqing Institute of Engineering, Chongqing, China.
Yingji LiSchool of Humanities and Management, Yunnan University of Chinese Medicine, Kunming, China.ORCID 0009-0009-6420-5391

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Social media platforms provide the public with a forum for interaction and communication with tourism destinations, playing a significant role in the shaping and dissemination of destination images. Similarly, social media plays a vital role in the construction and propagation of online images for higher education institutions. For instance, indicators such as likes, shares, and visits on Weibo can serve as measures of public engagement with university social media. To reveal the triggering rules of social media engagement by projected images of destinations and related factors, this paper builds a Bayesian model using data from posts and interactions on the official Sina Weibo account of a Chinese university from 2018 to 2023. This model simulates to infer the optimal decisions that trigger university social media engagement.

Indexed as

Social MediaBayes TheoremChinaCommunicationEmotionsHumansUniversities

Identifiers

PMID38626024
PMCPMC11020415

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.