Skip to contentScholarGate
LibraryBookshelfDeskReview StudioAssistant
Sign in
On this page
IntuitionHow it worksWhen to use itStrengths & limitationsCommon pitfallsApplicationsFrequently asked🔒 Read the full methodSourcesRelated methods
Cite this pageSpotted an issue on this page? Report or suggest a fix →
Home›Research Skills›Citation Analysis
Process / pipelineresearch-impact-metrics

Citation Analysis

Systematic Analysis of Citation Patterns and Research Impact · Also known as: citation metrics, bibliometric analysis, citation tracking

Citation analysis is the systematic study of how scholarly works are cited by subsequent research, used as a proxy for research impact and influence. Founded formally by Eugene Garfield in 1955 (introducing citation indexes), the field encompasses metrics ranging from simple citation counts to sophisticated indices like the H-index (Hirsch, 2005) and field-normalized indicators. Citation analysis is used to evaluate researcher productivity, track influence of ideas, assess journal quality, and detect research trends. While citation counts are not perfect measures of quality (high citation does not equal high quality; time lag in citation accumulation), they provide valuable quantitative data for research evaluation alongside peer review and expert assessment.

ScholarGate
  1. Process / pipeline
  2. v1
  3. 3 Sources
  4. PUBLISHED
Cite this page →
Tools & resources
Download slides
Learn & explore

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Method map

The neighbourhood of related methods — select a node to explore.

Citation Analysis
Altmetrics and Article-L…Citation Management ToolsDigital Object Identifie…ORCID Researcher Identif…Grey Literature SearchReference Management Sof…Systematic Search Strate…Time-sliced Citation ana…VOSviewer-assisted citat…

When to use it

Use citation analysis to: (1) evaluate the influence of your own publications (comparing your metrics over time), (2) benchmark your research against peer groups and career expectations, (3) identify influential articles and authors in your field, (4) assess journal quality and selectivity (via impact factor or CiteScore), (5) detect emerging research areas (via citation network analysis and trending topics), (6) evaluate research institutions or laboratories for funding decisions or hiring. Use citation metrics cautiously for career decisions (tenure, promotion): pair them with peer review, expert judgment, and other evidence of research quality. Avoid making publication decisions based on citation metrics alone; publish in journals appropriate to your research regardless of impact factor.

Strengths & limitations

Strengths
  • Quantifiable: citation counts are objective numbers, allowing comparison across researchers, institutions, and time periods.
  • Proxy for influence: citations (in theory) reflect how much subsequent research builds on prior work, indicating intellectual influence.
  • Available data: citation databases (Web of Science, Scopus, Google Scholar) contain billions of citations, enabling large-scale analyses.
  • Field-normalized variants: modern metrics (FWCI, CiteScore) account for differences in citation practices across disciplines, enabling fair cross-field comparisons.
  • Temporal insights: analyzing citation patterns over time reveals the trajectory of ideas, from emerging to established to obsolete.
Limitations
  • Does not measure quality: highly cited articles are not necessarily high-quality; citation count correlates weakly with methodological rigor or correctness.
  • Time lag: citation accumulation takes years; early-career researchers and recent publications appear less impactful than they will be long-term.
  • Field differences: biomedical research cites heavily; mathematics and physics cite sparingly. Cross-field comparisons without normalization are misleading.
  • Self-citation bias: researchers cite their own prior work, inflating personal citation metrics. Self-citations should be analyzed separately.
  • Publication bias: positive findings are cited more; negative and null results are undercited despite equal scientific importance. Meta-analyses and systematic reviews are cited more than primary studies.
  • Language and geographic bias: English-language articles and research from wealthy countries receive more citations. International and non-English research is undercited.
  • Gaming and manipulation: researchers can inflate citations through coordinated citation networks, predatory journals, or citation cartels. High citations do not guarantee authenticity.

Frequently asked

What is a good h-index?

Context-dependent. For biomedical researchers: h-index of 5–10 after 5 years is typical; 10–15 after 10 years; 20+ for senior researchers. For mathematicians and physicists: h-index is typically lower (field-specific norms); an h-index of 5 may be good. Always compare to peers in your field and career stage, not absolute thresholds.

If I have many self-citations, does that inflate my h-index unfairly?

Yes. Self-citations are legitimate (you do build on your own prior work), but self-citation rates vary widely. When evaluating researchers, view self-citation separately. Some databases now report h-indices with self-citations removed; compare both versions to assess inflated metrics.

My article was published 1 year ago but has zero citations. Does that mean it is not impactful?

Not necessarily. Citation accumulation takes time; most articles receive their first citation within 1–2 years. After 5 years, if your article still has zero citations, it may indicate limited impact, but even seminal works sometimes take years to be recognized.

Should I publish in a high-impact-factor journal to maximize my citations?

Publishing in a high-IF journal may increase visibility and citations, but it should not be your primary goal. Publish where your research is most appropriate and where the target audience is. A low-IF journal may be better-read by practitioners in your field. Quality of research matters more than journal prestige for long-term impact.

Sources

  1. Hirsch, J. E. (2005). An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572. DOI: 10.1073/pnas.0507655102 ↗
  2. Garfield, E. (1955). Citation indexes for science: A new dimension of bibliographic information. Science, 122(3159), 108–111. DOI: 10.1126/science.122.3159.108 ↗
  3. Egger, M., Davey Smith, G., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. BMJ, 315(7109), 629–634. DOI: 10.1136/bmj.315.7109.629 ↗

How to cite this page

ScholarGate. (2026, June 3). Systematic Analysis of Citation Patterns and Research Impact. ScholarGate. https://scholargate.app/en/research-skills/citation-analysis

Related methods

Altmetrics and Article-Level MetricsCitation Management ToolsDigital Object Identifier SystemORCID Researcher Identifier

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.

  • Altmetrics and Article-Level MetricsResearch Skills↔ compare
  • Citation Management ToolsResearch Skills↔ compare
  • Digital Object Identifier SystemResearch Skills↔ compare
  • ORCID Researcher IdentifierResearch Skills↔ compare
Compare side by side →

Referenced by

Altmetrics and Article-Level MetricsCitation Management ToolsDigital Object Identifier SystemGrey Literature SearchORCID Researcher IdentifierReference Management SoftwareSystematic Search StrategyTime-sliced Citation analysisVOSviewer-assisted citation analysis

Similar methods

H-IndexScientometric AnalysisJournal Impact FactorBibliometric AnalysisWeb of Science DatabaseAltmetrics and Article-Level MetricsCo-Citation AnalysisJournal Co-Citation Analysis

Related reference concepts

Citation AnalysisBibliometricsPageRank and HITS AlgorithmsEvaluation in Information RetrievalEvidence Hierarchies and Quality AppraisalCritical Appraisal and Individual Evidence Evaluation

Spotted an issue on this page? Report or suggest a fix →

ScholarGate — Citation Analysis (Systematic Analysis of Citation Patterns and Research Impact). Retrieved 2026-07-21 from https://scholargate.app/en/research-skills/citation-analysis · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Eugene Garfield (Citation Indexes, 1955); Jorge Hirsch (H-index, 2005)
Subfamily
research-impact-metrics
Year
1955 (citation indexes); 1975 (Impact Factor); 2005 (H-index)
Type
Tool
Related methods
Altmetrics and Article-Level MetricsCitation Management ToolsDigital Object Identifier SystemORCID Researcher Identifier
ScholarGate

A content-first reference library for research methods — what each one is, how it works, and where it comes from.

Open data (CC-BY)

Explore

  • Library
  • Search the library…
  • Browse by field
  • Fields
  • Journey
  • Compare
  • Which method?

Reference

  • Subjects
  • Atlas
  • Glossary
  • Methodology
  • Philosophy

Your tools

  • Bookshelf
  • Desk
  • Chat

Company

  • About
  • Pricing
  • Contact
  • Suggest a method

Entries are compiled from published sources for reference. Verifying the accuracy and suitability of any information for your own use remains your responsibility.

© 2026 ScholarGate · A research-method reference library
  • Privacy
  • Cookies
  • Terms
  • Delete account