Journal Self-Citation Analysis
Also known as: Self-Citation Rate Analysis, Journal Self-Referencing Analysis, Self-Citing and Self-Cited Rates, Citation Manipulation Detection
Journal self-citation analysis separates the citations a journal gives to itself from the citations it gives to and receives from the wider literature, in order to understand a journal's internal coherence and to detect potential inflation of impact metrics. Ronald Rousseau showed in 1999 that a journal's citation curve is really two curves superimposed: a self-citation component and an external-citation component, each with its own timing. Wolfgang Glänzel and colleagues, surveying the self-citation literature, distinguished the legitimate, communicative role of self-citation from its problematic use to manipulate indicators, and clarified how to measure its effect. The analysis revolves around two complementary rates: the self-cited rate, the share of a journal's incoming citations that come from itself, and the self-citing rate, the share of its outgoing references that point to itself. Comparing impact metrics with and without self-citations reveals how much a journal's standing depends on citing itself.
Key highlights
- Separates self-generated from externally generated citations, revealing how much of a journal's impact is independent.
- Provides two complementary rates, self-cited and self-citing, that answer distinct questions about impact and insularity.
- Rousseau's curve decomposition explains why self-citation disproportionately affects short-window metrics.
- Supports detection of anomalous self-citation used to inflate the impact factor, as applied by indexing services.
Intuition
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How it works
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When to use it
Use journal self-citation analysis when you need to assess the integrity of a journal's impact metrics, investigate suspected citation manipulation, or simply understand a journal's place between specialist coherence and insularity. It is appropriate for editors monitoring their own practices, for indexing services screening for anomalous self-citation, and for evaluators who want to judge a journal's external standing net of self-generated citations. The analysis requires citation data that identify the citing source for each citation, which standard databases provide. It is less meaningful for very small or very new journals where a few self-citations swing the rates, and it must be interpreted in disciplinary context, since normal self-citation levels vary widely across fields. Self-citation rates describe referencing behavior and should not by themselves be read as proof of misconduct.
Strengths & limitations
- Separates self-generated from externally generated citations, revealing how much of a journal's impact is independent.
- Provides two complementary rates, self-cited and self-citing, that answer distinct questions about impact and insularity.
- Rousseau's curve decomposition explains why self-citation disproportionately affects short-window metrics.
- Supports detection of anomalous self-citation used to inflate the impact factor, as applied by indexing services.
- Normal self-citation levels vary greatly by field, so a single threshold cannot flag manipulation across disciplines.
- Rates are unstable for small or new journals where a handful of self-citations dominate.
- High self-citation can be legitimate specialization, so the measure alone cannot prove intent to manipulate.
- Database definitions of the citing source and citable items affect the computed rates.
Common pitfalls
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Applications
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Frequently asked
What is the difference between the self-cited and self-citing rates?
The self-cited rate is the share of a journal's incoming citations that come from itself, measuring how much of its apparent impact is self-generated. The self-citing rate is the share of its outgoing references that point back to itself, measuring insularity. They are computed from opposite directions and answer different questions: a journal can receive few self-citations relative to its total impact (low self-cited rate) yet make many self-references (high self-citing rate), or vice versa. Both are needed for a full picture, and Rousseau treated the distinction as fundamental.
Is journal self-citation always a sign of manipulation?
No. Self-citation is often legitimate and even necessary: a specialized journal is the natural venue for follow-up work, and tightly knit subfields reference themselves heavily for sound scholarly reasons. Glänzel and colleagues emphasize this communicative role. Manipulation is suggested only when self-citation is anomalously high relative to disciplinary norms and concentrated in the short window that feeds the impact factor. Even then, high rates are a flag for investigation, not proof of intent; context, scope, and field norms must be weighed before drawing conclusions.
Why does self-citation affect the impact factor so strongly?
Because the impact factor uses a short two-year window and journals can cite their own brand-new articles immediately. Rousseau showed that the self-citation curve peaks earlier than the external-citation curve, so a large fraction of self-citations falls precisely within the window the impact factor counts. This means a journal can raise its impact factor by systematically citing its own recent papers, with disproportionate effect compared with the same self-citations spread over a longer period. Recomputing the impact factor with self-citations removed reveals how much of the headline number depends on this mechanism.
Sources
- 1.Glanzel, W., Debackere, K., Thijs, B., & Schubert, A. (2006). A concise review on the role of author self-citations in information science, bibliometrics and science policy. Scientometrics, 67(2), 263-277.
- 2.Rousseau, R. (1999). Temporal differences in self-citation rates of scientific journals. Scientometrics, 44(3), 521-531.
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Cite this page
ScholarGate. (2026, June 23). Journal Self-Citation Analysis. ScholarGate. https://scholargate.app/bibliometrics/journal-self-citation-analysis