Evidence map›Paper›PMID 35885173›Full record

ArticleEntropy (Basel, Switzerland)2022

Institution Publication Feature Analysis Based on Time-Series Clustering.

Weibin Lin, Mengwen Jin, Feng Ou, Zhengwei Wang, Xiaoji Wan, Hailin Li

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Weibin LinCollege of Business Administration, Huaqiao University, Quanzhou 362021, China.
Mengwen JinCollege of Business Administration, Huaqiao University, Quanzhou 362021, China.
Feng OuCollege of Business Administration, Huaqiao University, Quanzhou 362021, China.
Zhengwei WangCollege of Business Administration, Huaqiao University, Quanzhou 362021, China.
Xiaoji WanCollege of Business Administration, Huaqiao University, Quanzhou 362021, China.
Hailin LiCollege of Business Administration, Huaqiao University, Quanzhou 362021, China.ORCID 0000-0001-6924-9689

Funding

National Natural Science Foundation of China 71771094
6 · The paper itself

Abstract

Based on the time series of articles obtained from the literature, we propose three analysis methods to deeply examine the characteristics of these articles. This method can be used to analyze the construction and development of various disciplines in institutions, and to explore the features of the publications in important periodicals in the disciplines. By defining the concepts and methods relevant to research and discipline innovation, we propose three methods for analyzing the characteristics of agency publications: numerical distribution, trend, and correlation network analyses. The time series of the issuance of articles in 30 important journals in the field of management sciences were taken, and the new analysis methods were used to discover some valuable results. The results showed that by using the proposed methods to analyze the characteristics of institution publications, not only did we find similar levels of discipline development or similar trends in institutions, achieving a more reasonable division of the academic levels, but we also determined the preferences of the journals selected by the institutions, which provides a reference for subject construction and development.

Indexed as

associated networkfeature analysisinstitution publicationnumerical valuestime series clusteringtrend analysis

Identifiers

PMID35885173
PMCPMC9322065

What OpenQuestion holds

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LicenceCC BY
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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.