Chi-Sheng Chang1,2, Lifan Chen3, Tsair-Wei Chien4, Kun-Feng Tsai5*
1Quality Management Center, Linyin Chi-Mei Hospital, Tainan, Taiwan 2Department of Nursing, Min-Hwei College of Health Care Management, Tainan, Taiwan
3Department of Nursing, An Nan Hospital, China Medical University, Tainan, Taiwan
4Department of Medical Research, Chi Mei Medical Center, Taina, Taiwan
5Gastroenterology and Hepatology Section, Department of Internal Medicine, An Nan Hospital, China Medical University, Tainan, Taiwan.
*Corresponding Author: Kun-Feng Tsai,Gastroenterology and Hepatology Section, Department of Internal Medicine, An Nan Hospital, China Medical University, Tainan, No. 66, Sec. 2, Changhe Rd., Zhounan Village, Annan District, Tainan City, Taiwan
Received Date: 05 September 2026
Accepted Date: 05 October 2026
Published Date: 08 October 2026
Citation: Chang CS, Chen L, Chien TW, Tsai KF (2026) Scopus Cluster: A Web-Based Platform for Bibliometric Analysis of Scopus-Indexed Publications, with a Structural-hole analysis to the 2025 Top 2% Scientists in Gastroenterology and Hepatology. J Dig Dis Hepatol 11: 237. DOI: 10.29011/2574-3511.100237
Abstract
Background: Scopus-based bibliometric analysis often requires separate procedures for metadata preparation, network analysis, and visualization. Scopus Cluster is a browser-based platform that integrates these tasks and provides reporting of cluster structure, leadership concentration, and structural-hole positions. Methods: Scopus Cluster was applied to Scopus-indexed publications associated with 2,152 scientists in the 2025 Top 2% Scientists dataset for Gastroenterology and Hepatology, representing 54 countries and 1,220 institutions. Uploaded Scopus CSV meta data were transformed into automated summaries and more than 80 visualizations across authors, countries, institutions, departments, keywords, journals, publication years, document types, and cited references. Following-leading clustering algorithm (FLCA) networks were assessed using silhouette scores (SS) for local cluster separation, normalized modularity (Q) for global community structure, AAC for leadership concentration, and structural-hole measures of degree, effective size, and Burt constraint. Results: Scopus Cluster generated reports, forest plots, choropleth maps, Kano plots, slope plots, SS plots, Sankey diagrams, chord plots, and network visualizations within a unified workflow. Dr. Younossi showed substantial coauthor leadership concentration (AAC=0.93), whereas institutional collaboration was moderately concentrated (AAC=0.68). In the displayed first/corresponding-author network, Younossi also had the strongest structural-hole position, with the highest degree and effective size and the lowest Burt constraint. A composite structural-hole coefficient combined normalized degree, effective size, and inverse constraint; when all three components equaled 1, the composite AAC was 0.91. The outputs revealed geographic, institutional, thematic, temporal, and brokerage patterns not apparent from publication counts alone. Conclusions: Scopus Cluster provides an accessible and reproducible workflow for Scopus-based bibliometric analysis. By integrating FLCA, SS, Q, AAC, and structural-hole reporting, it complements conventional bibliometric software with transparent assessment of cluster quality, collaboration concentration, and network brokerage. Future studies should evaluate metadata quality, longitudinal change, and cross-database compatibility.
Keywords: Absolute Advantage Coefficient; Bibliometric Analysis; Following-leading clustering Algorithm; Scopus; Structural Hole