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Related Experiment Video

Updated: May 31, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Assigning Article-Level Themes in Bibliometric Analysis: Mode-Based Mapping Approach Using JMIR Aging Publications.

Sam Yu-Chieh Ho^1,2, Kang-Ting Tsai^3,4

¹Department of Emergency Medicine, Chi Mei Medical Center, No. 901, Chung Hwa Road, Yung Kung Dist, Tainan, Taiwan.

|May 28, 2026

Summary

This summary is machine-generated.

This study introduces the Theme Assignment Algorithm for Articles (TAAA) to map research themes to individual publications. The algorithm identified "DEMENTIA" as a consistent core theme in JMIR Aging, demonstrating its utility for bibliometric analysis.

Keywords:

FLCA clustering R programming bibliometric analysis following leader clustering algorithm theme assignment visual analytics

Related Experiment Videos

Last Updated: May 31, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Area of Science:

Bibliometrics and scientometrics
Information science
Computational social science

Background:

Bibliometric analysis commonly uses clustering to identify research themes.
A gap exists in systematically assigning these themes back to individual articles.
This limits interpretability and granular, article-level longitudinal analysis.

Purpose of the Study:

Introduce the Theme Assignment Algorithm for Articles (TAAA).
Develop a data-driven framework to map clustered themes to individual publications.
Identify dominant research patterns and thematic shifts within JMIR Aging.

Main Methods:

Applied TAAA to 434 JMIR Aging articles (2020-2025).
Harvested keywords from 3 sources: WoSCC Keywords Plus, author keywords, and abstract terms.
Grouped keywords into clusters using the "following leader clustering algorithm" and assigned primary themes via statistical modeling.

Main Results:

Identified 9, 7, and 9 core themes across the 3 keyword sources.
Prominent themes included HEALTH (39.4%), OLDER ADULTS (43.1%), and DEMENTIA (25.3%).
DEMENTIA consistently emerged as a core theme, validating TAAA's cross-source coherence and mapping capabilities.

Conclusions:

TAAA offers a replicable, scalable, and interpretable method for article-level thematic assignment.
The algorithm successfully identified consistent research patterns, such as the dominance of dementia studies in JMIR Aging.
TAAA has potential adaptability for other domains, including bioinformatics-inspired meta-analyses.