A leading author of meta-analysis does not have a dominant contribution to research based on the CJAL score: Bibliometric analysis

Abstract

Background: There have been nearly 200 thousand meta-analysis articles indexed by web of science (WoS) since 2013. To date, a bibliometric analysis of leading authors of meta-analyses that contribute to the field has not been conducted. Analyzing trend patterns in article citations and comparing individual research achievements (IRAs) are required following the extraction of meta-analysis articles. Using trend analysis, this study aims to verify the hypotheses that; The leading author has a dominant research achievement and; Recent articles that deserve worth reading can be identified. Methods: In the WoS collection, we identified the top 20 authors with the most articles related to meta-analysis. Using coword analysis, 2882 articles were collected to cluster author collaborations and identify the top 3 authors with the highest weighted centrality degrees. Based on the CJAL (category, journal raking by impact factor, authorship, and L-index on article citation) score and absolute advantage coefficient (AAC), we compared the IRAs and identified the author who dominated the field significantly beyond the next 2 authors. In WoS collection, coword analysis was used to highlight the characteristics of research domains for the top authors contributing to meta-analyses. The selection of articles that deserve reading is based on a temporal heatmap. Results: The top 2 authors were Young–Ho Lee (South Korea), Patompong Ungprasert (U.S.), and Brendon Stubbs (US) with CJAL scores of 240.71, 230.99, and 240.71, respectively. Based on the weak dominance coefficient (AAC = 0.49 < 0.50), it is evident that the leading meta-analysis author does not possess a significant dominant position over the next 2 leading authors in IRAs. Coword analysis was used to illustrate the characteristics of the 3 authors research domains. The 3 articles worth reading were selected based on a trend analysis of the last 4 years using the temporal heatmap. Conclusion: A coword analysis of meta-analysis studies identified 3 leading authors. There was no evidence that 1 author possessed a dominant position due to the lower AAC (=0.49 < 0.50) for the leading author. As we have demonstrated in this study, the CJAL score and the AAC can be applied to many bibliographical studies in the future.

Analyzing fulminant myocarditis research trends and characteristics using the follower-leading clustering algorithm (FLCA): A bibliometric study

“…The analysis comprised 3 main components: descriptive analytics, which involved identifying the most influential entities using CJAL scores [21] and analyzing publication trends, author collaborations (ACs) using the FLCA algorithm, and generating a dual map and timeline view of FM themes using the FLCA algorithm.…”

“…[18] It has proven successful in various fields of research. [19–21] While some research [12] has been conducted on the focus and thematic trends of fulminant myocarditis using CiteSpace [22] and VOSviewer, [23] there are certain limitations that need to be addressed in future studies. These limitations include the absence of cluster analysis to classify article themes and features, a lack of clarity in the author cocitation network related to FM, such as the utilization of timeline view, [24] time zone view, [25] and dual-map overlay of journals [26] using CiteSpace software, [17] and the absence of dashboard-type visualizations to provide readers with a comprehensive understanding of FM’s development over the past several decades.…”

A Comparative Analysis of Spine-Related Research Achievements between Authors in Neurology and Orthopedics: Differences in Productivity and Collaboration Patterns

“…ACs in bibliometrics can be analyzed using various metrics, such as coauthorship analysis, network analysis, and bibliographic coupling [10][11][12]. Coauthorship analysis examines the collaboration between authors, while network analysis visualizes the relationships between authors in a network graph.…”

“…To compare the research activities (RAs) of neurosurgeons and orthopedic surgeons, a CJAL score [21,22] that considers article category, journal impact factors (JIFs), authorships, and L-indices (on article citation) [23] is necessary. The second research question focuses on this RA comparison, which was based on the total CJAL scores and mean citations.…”

“…The calculation of the CJAL score [21,22] involves analyzing the publications of both the rst author (FP) and corresponding author (RP) [26], using a 4-quadrant plot [27] to display the leading entities in spine research. Generally, authors with more publications tend to have higher JCAL scores.…”