Bibliometrix-Assisted Citation Analysis
Also known as: bibliometrix citation analysis, R-based citation analysis, bibliometrix CA, citation analysis with bibliometrix
Bibliometrix-assisted citation analysis uses the bibliometrix R package to systematically retrieve, clean, and analyze citation data exported from major databases such as Web of Science and Scopus. By automating reference parsing, frequency counting, and network construction, it enables researchers to identify the most-cited works, map intellectual influence, and trace the evolution of scholarly fields at a scale that manual analysis cannot match.
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When to use it
Use bibliometrix-assisted citation analysis when you need to map the intellectual structure and citation landscape of an established research field using a reproducible, code-based workflow — particularly when the corpus is large (hundreds to thousands of documents) and the analysis needs to be auditable. It is well suited to systematic and bibliometric reviews that must report citation indicators for journals, authors, or documents, and to longitudinal studies tracking how citation patterns shift over time. Do not use it when the goal is to synthesise findings across studies (meta-analysis or qualitative synthesis is needed instead), when only a handful of papers exist in the field (manual screening is more appropriate), or when the researchers have no R programming experience and no access to the biblioshiny interface.
Strengths & limitations
- Open-source and freely available, making the analysis fully reproducible and auditable.
- Handles large corpora (thousands of records) that would be infeasible to analyse manually.
- Integrates multiple citation metrics — direct citations, co-citations, bibliographic coupling — within a single unified workflow.
- The biblioshiny Shiny app lowers the barrier to entry for researchers unfamiliar with R syntax.
- Supports multiple database sources (Web of Science, Scopus, PubMed, Lens.org) and normalises them automatically.
- Coverage depends entirely on the source database; papers not indexed by Web of Science or Scopus will be absent from the citation network.
- Citation counts reflect visibility and indexing, not necessarily scientific quality or correctness.
- Requires R installation and at least basic familiarity with R or the biblioshiny interface; not a point-and-click tool in its full form.
- Metadata quality varies across databases and time periods, requiring manual deduplication and cleaning before analysis.
Frequently asked
What databases does bibliometrix support?
Bibliometrix natively imports records from Web of Science (plain text and tab-delimited formats), Scopus (CSV), PubMed (XML and txt), and Lens.org (CSV), among others. The convert2df() function detects the source format automatically. Coverage and metadata completeness vary by database, so analysts often combine exports from multiple sources and deduplicate.
How is bibliometrix-assisted citation analysis different from using VOSviewer?
Both tools perform citation-based network analysis, but they differ in workflow and depth. Bibliometrix operates within R and provides a complete programmatic pipeline from data import through statistical analysis to visualisation, making it fully reproducible and extensible. VOSviewer is a standalone application focused primarily on visualisation and clustering of co-citation and co-authorship networks; it is easier to use for non-programmers but offers less flexibility for custom analyses and statistical reporting.
Do I need to know R to use bibliometrix?
Basic R knowledge is sufficient to run standard analyses. The biblioshiny() function launches a browser-based Shiny application that provides a graphical interface covering most common analyses — data import, descriptive statistics, network construction, and visualisation — without writing R code. For custom or advanced analyses, R scripting is required.
How large a corpus can bibliometrix handle?
Bibliometrix handles corpora of tens of thousands of records on a standard desktop or laptop computer. Performance depends on available RAM; corpora above 50,000 records may require memory optimisation or a machine with at least 16 GB RAM for network construction steps. For most systematic and bibliometric reviews, which typically work with hundreds to a few thousand records, performance is not a practical concern.
Is bibliometrix-assisted citation analysis the same as a systematic review?
No. Citation analysis maps the quantitative citation structure of a field — which papers are most-cited, how influence flows, which clusters of work exist — but it does not synthesise the substantive findings of individual studies. A systematic review evaluates and synthesises study results to answer a focused research question. Bibliometrix-assisted citation analysis is often used as a preliminary or complementary step within a broader bibliometric review, not as a substitute for content synthesis.
Sources
- Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. DOI: 10.1016/j.joi.2017.08.007 ↗
- Garfield, E. (1955). Citation indexes for science: A new dimension in documentation through association of ideas. Science, 122(3159), 108–111. DOI: 10.1126/science.122.3159.108 ↗
How to cite this page
ScholarGate. (2026, June 3). Bibliometrix-Assisted Citation Analysis. ScholarGate. https://scholargate.app/en/scientometrics/bibliometrix-assisted-citation-analysis
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Bibliographic CouplingBibliometrics↔ compare
- Bibliometric AnalysisScientometrics↔ compare
- Co-Citation AnalysisBibliometrics↔ compare
- Science MappingBibliometrics↔ compare
- Scientometric AnalysisScientometrics↔ compare
- Systematic Literature ReviewScientometrics↔ compare