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Updated: Sep 5, 2025

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
Using the forest plot to compare citation achievements in bibliographic and meta-analysis studies since 2011 using
Jian-Wei Wu1,2, Tsair-Wei Chien3, Ya-Ching Tsai4
1Department of Family Medicine, Kaohsiung Veterans General Hospital, Kaohsiung City, Taiwan.
Background:
We saw a steady increase in the number of bibliographic studies published over the years. The reason for this rise is attributed to the better accessibility of bibliographic data and software packages that specialize in bibliographic analyses. Any difference in citation achievements between bibliographic and meta-analysis studies observed so far need to be verified. In this study, we aimed to identify the frequently observed MeSH terms in these 2 types of study and investigate whether the highlighted MeSH terms are strongly associated with one of the study types.
Methods:
By searching the PubMed Central database, 5121 articles relevant to bibliometric and meta-analysis studies were downloaded since 2011. Social network analysis was applied to highlight the major MeSH terms of quantitative and statistical methods in these 2 types of studies. MeSH terms were then individually tested for any differences in event counts over the years between study types using odds of 95% confidence intervals for comparison.
Results:
In these 2 studies, we found that the most productive countries were the United States (19.9%), followed by the United Kingdom (8.8%) and China (8.7%); the most number of articles were published in PLoS One (2.9%), Stat Med (2.5%), and Res Synth (2.4%); and the most frequently observed MeSH terms were statistics and numerical data in bibliographic studies and methods in meta-analysis. Differences were found when compared to the event counts and the citation achievements in these 2 study types.
Conclusion:
The breakthrough was made by developing a dashboard using forest plots to display the difference in event counts. The visualization of the observed MeSH terms could be replicated for future academic pursuits and applications in other disciplines using the odds of 95% confidence intervals.
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