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Updated: Mar 21, 2026
05:02
Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
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How Is My Field Evolving? - Network Based Analysis of Biomedical Scientific Discourse
Cord Spreckelsen1, Klaus Kabino1
1Department of Medical Informatics, RWTH Aachen University.
Studies in Health Technology and Informatics
|May 4, 2016
Summary
Bibliometric data analysis using a new pipeline helps scientists understand research trends. This method visualizes thematic evolution, highlighting key areas like electronic health records in clinical decision support systems.
Area of Science:
- Biomedical informatics
- Bibliometrics
- Network analysis
Background:
- The rapid growth of scientific publications makes it difficult to grasp the overview of a research field.
- Computer-supported discourse analysis using bibliometric data can aid researchers in identifying key focus areas and emerging trends.
Purpose of the Study:
- To develop an automated processing pipeline for analyzing scientific literature.
- To visualize the thematic evolution within a research domain for enhanced interpretation.
Main Methods:
- A four-step pipeline involving data acquisition from PubMed, data preprocessing, and network analysis of co-occurring keywords.
- Utilizing degree and betweenness centrality for keyword analysis.
- Visualizing results using heatmap diagrams.
Main Results:
- Analysis of clinical decision support systems using 5,094 PubMed results revealed 174,663 inter-keyword links.
- The generated heatmap indicated a growing relevance of terms such as 'electronic health record' and '(patients') age'.
Conclusions:
- Network-based discourse analysis is feasible through an efficient processing pipeline.
- This approach offers valuable insights into the thematic progression of scientific fields.
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