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Updated: Jul 2, 2026
05:02
Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
TREND: a tool for rapid online research literature analysis and quantification
1Psychology Department, University of Minnesota, Twin Cities, Minnesota 55455, USA. rlanders@umn.edu
Behavior Research Methods
|August 14, 2008
Summary
The Research Explicator for oNline Databases (TREND) tool quickly quantifies large research literatures from online databases. It helps researchers and educators identify key articles and authors, boosting productivity in literature reviews and reading list creation.
Area of Science:
- Bibliometrics
- Information Science
- Research Methodology
Background:
- Assessing large research literatures is time-consuming.
- Existing methods lack speed and objectivity for online database outputs.
- Need for efficient tools to analyze research trends.
Purpose of the Study:
- Introduce the Research Explicator for oNline Databases (TREND) tool.
- Demonstrate TREND's capability to rapidly and objectively quantify research literature.
- Highlight TREND's utility for researchers and educators.
Main Methods:
- TREND parses output from online research databases.
- The tool extracts key bibliometric data: highly cited articles, frequent authors, publication dates.
- A case study addresses challenges in processing non-standard citations (e.g., Baron & Kenny, 1986).
Main Results:
- TREND enables rapid extraction of core information from large datasets (thousands of articles).
- Identifies most cited articles, prolific authors, and publication date distributions.
- Demonstrates feasibility of automated analysis despite citation formatting variations.
Conclusions:
- TREND significantly increases productivity for literature reviews and curriculum development.
- The tool offers objective insights into research landscapes.
- Automated bibliometric analysis is viable, though citation parsing requires careful handling.
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