Bibliometrix-Assisted Narrative Review
Also known as: bibliometrix narrative review, R-bibliometrix narrative synthesis, quantitative-assisted narrative review
A bibliometrix-assisted narrative review combines the quantitative field-mapping capabilities of the bibliometrix R package with the interpretive flexibility of a traditional narrative review. Bibliometric indicators — publication trends, author and country productivity, co-citation networks, keyword co-occurrence — are computed and visualised first to orient the reviewer, then a discursive, thematic narrative synthesises the intellectual content of key sources. The result is a structured yet flexible overview of a field that is more transparent and reproducible than a purely informal narrative.
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When to use it
Use a bibliometrix-assisted narrative review when you want a transparent, data-informed overview of a research field but do not need the exhaustive screening protocol of a systematic review. It is well suited to broad thematic questions, field overviews for introductory chapters, and reviews of interdisciplinary or rapidly evolving topics where rigid inclusion criteria would miss important work. The method requires a database export (Web of Science or Scopus access) and basic R skills or willingness to use the biblioshiny graphical interface. Do not use it as a substitute for a systematic review or meta-analysis when the goal is to answer a precise clinical or policy question from pooled evidence — the lack of formal screening and quality assessment makes it unsuitable for guideline development or clinical decision support.
Strengths & limitations
- Provides a transparent, reproducible quantitative foundation that is absent in purely informal narrative reviews.
- Rapidly maps an entire field's output — identifying key authors, journals, and thematic clusters — without manual screening of thousands of abstracts.
- Flexible scope accommodates broad thematic questions and interdisciplinary topics that resist narrow PICO framing.
- Visualisations (keyword maps, citation networks) communicate field structure clearly to readers unfamiliar with the literature.
- The bibliometrix R package is open-source, well-documented, and actively maintained, lowering the barrier to implementation.
- Coverage depends on database availability; studies not indexed in Web of Science or Scopus may be missed, creating publication-language and discipline bias.
- No formal quality appraisal of included studies; the narrative may inadvertently over-weight high-citation work rather than high-quality work.
- The narrative synthesis component is harder to replicate than a fully systematic protocol, reducing methodological transparency.
- Requires at least basic R proficiency or familiarity with the biblioshiny interface; reviewers without quantitative backgrounds may find the setup non-trivial.
Frequently asked
Is a bibliometrix-assisted narrative review publishable in peer-reviewed journals?
Yes. Many journals in management, information science, education, and health-related disciplines publish this type of review. Reviewers typically expect a clear description of the search strategy, the bibliometric methods applied, and the criteria used to select papers for deep reading. Transparency about what was and was not done systematically is key to acceptance.
Do I need to code in R, or can I use a graphical interface?
The bibliometrix package offers biblioshiny, a Shiny-based web application that exposes most core analyses through a point-and-click interface. You still need R and the bibliometrix package installed, but you can run analyses without writing R code. For more customised outputs or automation, scripting is preferable.
How is this different from a bibliometric analysis alone?
A standalone bibliometric analysis stops at quantitative indicators — counts, networks, and maps — without providing a substantive narrative about what the papers say. The bibliometrix-assisted narrative review uses those indicators to orient a critical, discursive synthesis of the literature's intellectual content. The bibliometric component is a means of scoping; the narrative is the scholarly contribution.
How many records do I need for the bibliometric component to be meaningful?
There is no strict minimum, but co-citation networks and keyword co-occurrence maps become interpretable only with at least 50–100 records. Very sparse datasets (fewer than 30 records) produce unstable network structures. If the field is genuinely small, simpler citation counts and author statistics may be more informative than network visualisations.
Can I use Google Scholar exports instead of Web of Science or Scopus?
Bibliometrix is designed to work with Web of Science and Scopus exports and also supports PubMed, Dimensions, and a few other sources. Google Scholar does not currently offer a structured bulk export compatible with bibliometrix. If institutional access to WoS or Scopus is unavailable, the OpenAlex or Lens.org APIs can export structured records that some bibliometric tools accept.
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 ↗
- Green, B. N., Johnson, C. D., & Adams, A. (2006). Writing narrative literature reviews for peer-reviewed journals: secrets of the trade. Journal of Chiropractic Medicine, 5(3), 101–117. DOI: 10.1016/S0899-3467(07)60142-6 ↗
How to cite this page
ScholarGate. (2026, June 3). Bibliometrix-Assisted Narrative Review. ScholarGate. https://scholargate.app/en/scientometrics/bibliometrix-assisted-narrative-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
- Narrative ReviewScientometrics↔ compare
- Science MappingBibliometrics↔ compare
- Scoping ReviewScientometrics↔ compare
- Systematic Literature ReviewScientometrics↔ compare