Applying Gini coefficient to evaluate the author research domains associated with the ordering of author names: A bibliometric study. Issue 39 (September 2018)

• Record Type: Journal Article
• Authors: Chien, Tsair-Wei; Chow, Julie Chi; Chang, Yu; Chou, Willy
• Other Names: Hoang. Minh Van section editor.
• Is Part Of: Medicine. Volume 97:Issue 39(2018)
• Publication Date: 2018-09
• Subjects: authorship collaboration -- Gini coefficient -- Google Maps -- personal impact factor -- PubMed library -- social network analysis; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000012418
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract: Background: Team 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. Methods: By 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. Results: The 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). Conclusion: Results 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.