Evaluating the research domain and achievement for a productive researcher who published 114 sole-author articles : A bibliometric analysis

Abstract

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Abstract

Background:

Team science research includes authors from various fields collaborating to publish their work on certain topics. Despite the numerous papers that discussed the ordering of author names and the contributions of authors to an article, no paper evaluated

• (1)

  the research achievement (RA) and

• (2)

  the research domain (RD) for productive sole-author researchers.

In addition, few researchers publish academic articles without co-author collaboration. Whether the bibliometric indexes (eg, h-/x-index) of sole-author researchers are higher than those of other types of multiple authors is required for comparison. We aimed to evaluate a productive author who published 114 sole-author articles with exceptional RA and RD in academics.

Methods:

By searching the PubMed database (Pubmed.com), we used the keyword of (Taiwan[affiliation]) from 2016 to 2017 and downloaded 29,356 articles. One physician (Dr. Tseng from the field of Internal Medicine) who published 12 articles as a single author was selected. His articles and citations were searched in PubMed. A comparison of various types of author ordering placements was conducted using sensitivity analysis to inspect whether this sole author earns the highest metrics in RA. Social network analysis (SNA), Gini coefficient (GC), pyramid plot, and the Kano diagram were applied to gather the following data for visualization:

• (1)

  the author collaborations and RA using x-index;

• (2)

  the author's article-related journals frequently published in the past;

• (3)

  the most influential medical subject heading (MeSH) using citation analysis to denote the author's RD.

Results:

We observed that

• (1)

  DR Tseng contributed 114 sole-author articles in 140 publications (=81.4%) since 2002;

• (2)

  the 100% sole-author scenario earned the highest h-/x-index;

• (3)

  the author's RD includes epidemiology, complications, and metabolism with an exceptional GC (=0.55).

Conclusions:

The metrics on RA are high for the sole author studied. The author's RD can be denoted by the MeSH terms and measured by the GC. The author-weighted scheme is required for quantifying author credits in an article to evaluate the author's RA. Social network analysis incorporating the Kano diagrams provided insights into the relationships between actors (eg, coauthors, MeSH terms, or journals). The methods used in this study can be replicated to evaluate other productive studies on RA and RD in the future.