ArticleMedicine2018
Applying Gini coefficient to evaluate the author research domains associated with the ordering of author names: A bibliometric study.
Article in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Article
- A Bibliometric Analysis on Dengue Outbreaks in Tropical and Sub-Tropical Climates Worldwide Since 1950.International journal of environmental research and public health · 2021Article
- Using Kano diagrams to display the most cited article types, affiliated countries, authors and MeSH terms on spinal surgery in recent 12 years.European journal of medical research · 2021Review
- Article
- The Most-Cited Authors Who Published Papers in JMIR mHealth and uHealth Using the Authorship-Weighted Scheme: Bibliometric Analysis.JMIR mHealth and uHealth · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTeam science research includes the number of coauthors in publications. Many papers have discussed the ordering of author names and the contributions of authors to a paper. However, no paper addresses the relation between authors' research domains and personal impact factors (PIF) with the ordering of author names. We aimed to apply Gini coefficient (GC) to evaluate the author research domains associated with the PIF and the ordering of author names on academic papers.
methodsBy searching the PubMed database (Pubmed.com), we used the keyword "medicine" [journal] and downloaded 10,854 articles published from 1969 to 2018. A total number of 7502 articles labeled with complete author's countries/areas were included in data analysis. We also proposed a PIF index and jointly applied social network analysis (SNA), the GC, and Google Maps to report the following data with visual representations: the trend of author collaboration in Medicine; the dominant nations and keywords in Medicine; and the author research domains in Medicine associated with the PIF and the ordering of author names on academic papers.
resultsThe trend of author collaboration in Medicine is slightly declining (= -0.06) based on the number of authors per article. The mean number of individuals listed as authors in articles is 7.5. Most first authors are from China (3649, 48.64%) and Taiwan (847, 11.29%). The median of GC (0.32) and PIF (0.74) for the middle authors are obviously less than those for the first (0.53, 2.19) and the last authors (0.42, 2.61). A perfect positive linear relation with a large effect exists between GC and PIF because the correlation coefficient is 0.68 (>0.50, t = 2.48, n = 9).
conclusionResults suggest that the corresponding author is submitting the manuscript to the target journal with a core author's academic background and the personal impact factor related to the research domain and the journal scope in the future. As such, peer reviewers can quickly determine whether the manuscript is a potentially citable research paper.
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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.