Evidence map›Paper›PMID 41107305›Full record

ArticleScientific reports2025

Optimizing short video strategies for intelligent communication in university campus culture construction using circular intuitionistic fuzzy COCOFISO modeling.

Qian Li

Abstract read
In one paragraph

Article in Scientific reports, 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

1 author.

Qian LiLiaocheng University Dongchang College, Liaocheng, 252000, Shandong, China. lqian5515@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Short-video communication is becoming a more common tool in universities to influence campus culture, but the choice of strategies and tools is not a straightforward one due to the variety of goals at particular institutions, limited resources, and the lack of reliability in expert advice. The paper proposes a circular intuitionistic fuzzy combined compromise solution to the ideal solution optimization (C-IF COCOFISO) method for ranking candidate short-video strategies based on a number of possibly conflicting criteria. Modelling the expert judgments as circular intuitionistic fuzzy constructions, which are combined and their aggregation is performed in a manner incorporating a combined compromise solution to ideal solution optimization (COCOFISO) procedure, led to consistently stable and easily interpretable priority scores. The criteria include the suitability of cultural relevance, effectiveness in communication, flexibility in technology, opportunities for student engagement, ethics, and sustainability. The framework consolidates fuzzy expressed fuzzy modelling and a clear-cut compromise-driven ranking pipeline, enabling decision-makers to handle waffling and trade-offs in one process. In particular, it combines C-IF data with COCOFISO to overcome competing goals and incomplete decisions, offers a step-by-step procedure that produces reproducible weights and rankings that are appropriate to institutional planning, and is tested on an actual university case, including sensitivity and cross-method comparisons. The findings show that C-IF COCOFISO provides a similar ranking and is more sensitive to cultural goals than the minimal requirements of decision-making processes, making it a flexible and convenient tool for drawing short-video communication plans in higher education.

Indexed as

Campus culture constructionCircular intuitionistic fuzzy COCOFISODecision-makingShort video strategies

Identifiers

PMID41107305
PMCPMC12534412

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.