Journal Co-Citation Analysis
Also known as: journal citation mapping, journal network analysis, cited source co-citation
Journal co-citation analysis is a bibliometric method that maps the intellectual structure of a research field by analyzing how frequently pairs of journals are cited together in the same papers. Two journals are co-cited when papers cite both journals, indicating that the journals are perceived as intellectually related by the citing authors. This extension of paper-level co-citation analysis to the journal level reveals the topological structure of journal relationships, disciplinary boundaries, and the role of different journals within research communities.
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When to use it
Use journal co-citation analysis to assess the intellectual structure of a research field and identify core journals that define it, to understand disciplinary identity and boundaries, to position a journal within a research landscape (core, peripheral, or bridging), to detect interdisciplinary connections between research communities, or to understand how fields reorganize over time. It is valuable for journal editors assessing their journal's scope and competitive position, for librarians making subscription decisions, for researchers identifying key reading lists, and for research policy makers understanding field organization. Journal co-citation analysis complements paper-level analysis by revealing macro-structure (which journal communities exist) versus paper-level micro-structure (which papers are similar).
Strengths & limitations
- Macro-level perspective: aggregates intellectual relationships across many papers, revealing high-level field structure.
- Stability: journal identity is more stable than paper focus; journal networks change slowly, enabling longitudinal analysis.
- Practical utility: journal selection is important for researchers and librarians; co-citation network directly informs this decision.
- Discipline differences are visible: comparing journal networks across fields reveals disciplinary organization (distributed vs. hierarchical, interdisciplinary vs. siloed).
- Scalable: journal networks contain 100–1000 nodes (manageable visually); far fewer than paper networks with thousands of nodes.
- Aggregation loss: co-citation at journal level obscures variation within journals. A journal may contain diverse research; co-citation conflates all papers in a journal.
- Journal name standardization: title changes, abbreviations, and misspellings require careful standardization; errors fragment co-citation counts across variations of the same journal.
- Citation bias affects journals selectively: some journals cite journals heavily (reviews, survey articles), while others (e.g., pure theory) cite books and preprints; selective analysis of one journal type may distort co-citation structure.
- Open-access and database coverage: journals indexed in Web of Science or Scopus are visible; non-indexed journals are invisible, distorting the network.
Frequently asked
How does journal co-citation analysis differ from journal impact factor?
Impact Factor (average citations per paper) measures a journal's average influence; it is a one-dimensional metric. Journal co-citation analysis measures how a journal relates to other journals intellectually; it is a network metric. A journal with moderate Impact Factor (e.g., IF=3) might have high betweenness centrality (bridge between two fields), making it strategically important despite lower citation count. Conversely, a high-IF journal might be cited in isolation (no co-citation with others), indicating specialized prestige but little intellectual connection to broader research. Use both metrics together: IF for influence, co-citation for structural position.
Should I analyze all journals in a field or focus on a subset?
Start with all journals in your target literature (papers from a query or field). Thresholding by minimum co-citation frequency (e.g., >3) will naturally exclude peripheral journals with minimal citations. Alternatively, include only journals with Impact Factor >1.5 or quartile ranking, though this introduces bias toward established journals. For comprehensive landscape mapping, include all journals; for focused analysis (core journals only), apply thresholds. Always report which journals were included and why.
Can journal co-citation networks predict which journals will become influential?
Not directly. Co-citation networks are descriptive (show current structure). However, temporal analysis (comparing networks across decades) reveals trends: journals with rising centrality or growing co-citation with high-impact journals are increasing in influence. Combine co-citation analysis with publication growth trends and citation trends to identify ascending journals. A journal with rising publication count + rising co-citation centrality + rising impact factor is likely becoming more influential.
How do I account for the fact that major journals cite each other heavily?
High-impact journals (Science, Nature, JAMA) cite each other frequently due to prestige; this creates artificial clustering of these journals. To address: (1) weight co-citations inversely by individual journal citation frequency (normalization), (2) analyze separate networks for cited sources vs. citing journals (reverse direction), or (3) exclude universally high-cited journals and analyze the remaining network. There is no universal fix; report which approach you used and how it affected results.
Sources
- White, H. D., & Griffith, B. C. (1981). Author co-citation: A literature measure of intellectual structure. Journal of the American Society for Information Science, 32(3), 163–171. DOI: 10.1002/asi.4630320302 ↗
- McCain, K. W. (1990). Mapping authors in intellectual space: A technical overview. Journal of the American Society for Information Science, 41(6), 433–443. DOI: 10.1002/(SICI)1097-4571(199009)41:6<433::AID-ASI11>3.0.CO;2-Q ↗
How to cite this page
ScholarGate. (2026, June 4). Journal Co-Citation Analysis. ScholarGate. https://scholargate.app/en/bibliometrics/journal-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
- Co-Citation AnalysisBibliometrics↔ compare
- Keyword Co-Occurrence AnalysisBibliometrics↔ compare
- Science MappingBibliometrics↔ compare