bibliometrix-Assisted Systematic Literature Review
Also known as: bibliometrix SLR, R-bibliometrix systematic review, bibliometrix-based literature review, bibliometrix-enhanced SLR
A bibliometrix-assisted systematic literature review integrates the R package bibliometrix — developed by Aria and Cuccurullo (2017) — into the standard systematic review pipeline to automate and visualize bibliometric performance and science-mapping analyses. It combines the transparency and reproducibility of a protocol-driven systematic search with quantitative tools for tracking publication trends, author collaboration networks, keyword co-occurrence, and thematic evolution across a field.
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When to use it
Use this approach when the primary goal is both to synthesise evidence on a topic and to characterise the intellectual landscape of a research field — for example, when conducting a research-agenda paper, a doctoral literature review, or a discipline-level state-of-the-art assessment. It is especially suited when the corpus is large (hundreds to thousands of records) and manual tracking of citation patterns is impractical. The method requires exportable bibliographic records from databases that provide citation and affiliation metadata; it is less appropriate when the corpus is small (fewer than roughly 50 records), when the research question demands qualitative depth rather than field-level mapping, or when the target database does not export structured metadata compatible with bibliometrix. Do not use it as a substitute for rigorous eligibility screening: the bibliometric layer enriches but does not replace content-level appraisal.
Strengths & limitations
- Automates time-consuming bibliometric calculations — publication trends, citation counts, h-indices, and collaboration networks — within a reproducible R workflow.
- Produces rich visual outputs (network maps, thematic cluster diagrams, country collaboration maps) that convey field structure at a glance.
- Scales efficiently to large corpora of hundreds or thousands of records that would be unmanageable by hand.
- The Biblioshiny interface lowers the R programming barrier, making the tool accessible to researchers without scripting experience.
- Fully reproducible: the R script and dataset constitute an auditable record of every analytical step.
- Analysis quality depends entirely on the completeness and accuracy of the exported bibliographic metadata; databases with partial citation data (e.g., Google Scholar) are not well supported.
- Bibliometric indicators (citation counts, h-index) are sensitive to field size, publication age, and indexing practices, and must be interpreted with appropriate caution.
- The package does not perform qualitative content analysis or risk-of-bias assessment; those stages still require human judgment.
- Results are contingent on which databases are searched; a corpus limited to Web of Science will miss literature indexed only in Scopus or PubMed.
Frequently asked
Do I need to know R programming to use bibliometrix?
Basic R familiarity is helpful but not essential. The Biblioshiny web interface, launched from within R with a single command, provides a fully graphical, point-and-click version of the main bibliometrix analyses. Researchers comfortable with spreadsheets and standard statistical software typically find Biblioshiny accessible with minimal learning time.
Which databases are compatible with bibliometrix?
bibliometrix natively reads export files from Web of Science (plain text format), Scopus (CSV or BibTeX), PubMed (XML or nbib), and several other sources. The convert2df() function handles format detection automatically. Google Scholar is not directly compatible because it does not export structured citation metadata.
How is this method different from a standard bibliometric analysis?
A standalone bibliometric analysis typically operates on a broad, unscreened corpus retrieved from a database and focuses on quantitative field mapping. A bibliometrix-assisted systematic literature review layers bibliometric analysis onto a protocol-driven, eligibility-screened review process. The systematic component ensures the evidence base is transparent and reproducible; the bibliometrix component adds quantitative field characterisation that a traditional SLR does not provide.
Should I report the bibliometrix analyses using PRISMA or a separate reporting guideline?
The systematic search and screening stages should follow PRISMA 2020 reporting standards, including a flow diagram. The bibliometric analysis layer does not yet have a universally adopted reporting standard, but leading journals expect disclosure of the database version, export date, the specific bibliometrix functions applied, and the R/package version used, so that another researcher could reproduce the analysis exactly.
Can bibliometrix handle non-English literature?
bibliometrix processes whatever metadata the source database provides. If the database indexes non-English records with English-language metadata fields (title, abstract, keywords), these can be analysed. However, keyword co-occurrence and thematic analyses based on author keywords may be distorted when the corpus mixes multiple languages, since the same concept may appear under different terms. Restricting analyses to the English-language metadata fields or pre-translating keywords mitigates this.
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 ↗
- Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLOS Medicine, 6(7), e1000097. DOI: 10.1371/journal.pmed.1000097 ↗
How to cite this page
ScholarGate. (2026, June 3). bibliometrix-Assisted Systematic Literature Review. ScholarGate. https://scholargate.app/en/scientometrics/bibliometrix-assisted-systematic-literature-review
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.
- Bibliometric AnalysisScientometrics↔ compare
- Co-Citation AnalysisBibliometrics↔ compare
- Science MappingBibliometrics↔ compare
- Scientometric AnalysisScientometrics↔ compare
- Systematic Literature ReviewScientometrics↔ compare
- VOSviewer-assisted systematic literature reviewScientometrics↔ compare