PRISMA-Compliant Co-Citation Analysis
Also known as: systematic co-citation review, PRISMA co-citation, co-citation analysis with PRISMA reporting, transparent co-citation analysis
PRISMA-compliant co-citation analysis is a systematic bibliometric method that applies the PRISMA 2020 reporting framework to co-citation analysis. It identifies intellectual clusters in a research field by measuring how frequently pairs of documents are cited together, while ensuring full transparency of the literature search, screening decisions, and analytic choices through a pre-registered protocol and standardised flow diagram.
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When to use it
Use PRISMA-compliant co-citation analysis when the goal is to map the intellectual structure of a research field — identifying foundational documents and the thematic clusters they define — while meeting the transparency and reproducibility standards expected by high-impact journals. It is best suited to mature fields with an existing citation record of at least several hundred articles in the target databases. The method requires access to a citation database that exports reference lists (Web of Science or Scopus), proficiency with a bibliometric tool (VOSviewer, bibliometrix in R, or CiteSpace), and willingness to follow a multi-stage PRISMA screening process. Do not use it when fewer than 100 source documents are available (co-citation matrices become sparse), when the research question concerns effect sizes or intervention outcomes rather than intellectual structure, or when a rapid turnaround is needed — full PRISMA compliance adds substantial time.
Strengths & limitations
- Produces a reproducible, auditable record of how the literature was identified and analysed, satisfying the requirements of systematic-review journals.
- Reveals the historical and intellectual foundations of a field by surfacing documents that are consistently co-cited, not merely highly cited.
- Combines quantitative rigour (co-citation matrices, clustering) with interpretive depth (cluster labelling and narrative description).
- The PRISMA flow diagram makes inclusion and exclusion decisions transparent, reducing selection bias relative to informal literature reviews.
- Pre-registration of the protocol prevents outcome-reporting bias in bibliometric research.
- Co-citation patterns reflect past influence; very recent publications are under-cited and will not appear in well-defined clusters regardless of their importance.
- Full PRISMA compliance is resource-intensive: dual screening, protocol registration, and detailed reporting require substantially more time than a standard bibliometric analysis.
- Coverage depends on the selected database; papers indexed only in Google Scholar, PubMed, or subject-specific repositories may be missed.
- Clustering results are sensitive to the choice of threshold, normalisation method, and algorithm, yet PRISMA does not yet provide standardised guidance specific to bibliometric methods.
Frequently asked
Is PRISMA designed for bibliometric studies?
PRISMA was originally developed for clinical systematic reviews and meta-analyses, but its core principles — pre-specified protocol, transparent search, explicit screening, and full reporting — are directly applicable to any systematic literature study, including bibliometric reviews. Several methodologists have adapted and extended the PRISMA framework specifically for bibliometric research.
How does co-citation analysis differ from citation analysis?
Citation analysis counts how many times each document is cited (measuring impact). Co-citation analysis counts how often pairs of documents are cited together by later work (measuring intellectual proximity). The two methods answer different questions: citation analysis ranks influence; co-citation analysis maps the relational structure of ideas.
What is a good minimum co-citation threshold?
A common starting point is a minimum co-citation count of 5 (meaning the pair must be co-cited in at least 5 different articles), but this depends on corpus size. In large corpora a threshold of 10 or higher reduces noise. The threshold should be decided before analysis and stated in the protocol, not tuned to obtain a preferred visual output.
Which tools support PRISMA-compliant co-citation analysis?
VOSviewer is widely used for co-citation network construction and visualisation. The bibliometrix package in R provides comprehensive co-citation analysis alongside PRISMA-compatible reporting exports. CiteSpace is another option, particularly popular in health and social science fields. Rayyan or Covidence can support the PRISMA screening stages.
Do I need two independent screeners?
For a fully PRISMA-compliant review, dual independent screening is the expected standard, with inter-rater reliability reported (e.g., Cohen's kappa). In practice, many published bibliometric reviews use single screening with a random sample checked by a second reviewer. Journals vary in their requirements; check the target journal's instructions for authors.
Sources
- Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372, n71. DOI: 10.1136/bmj.n71 ↗
- Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4), 265-269. DOI: 10.1002/asi.4630240406 ↗
How to cite this page
ScholarGate. (2026, June 3). PRISMA-Compliant Co-Citation Analysis. ScholarGate. https://scholargate.app/en/scientometrics/prisma-compliant-co-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
- PRISMA-based reviewScientometrics↔ compare
- Science MappingBibliometrics↔ compare
- Systematic Literature ReviewScientometrics↔ compare