CASRAI Dictionary

Tag: CiteScore

  • Scopus vs Web of Science: Bibliographic Databases Compared

    Scopus is Elsevier’s large multidisciplinary abstract and citation database, and it is the principal alternative to Clarivate’s Web of Science for tracking scholarly literature and its citation relationships. Both index peer-reviewed publications and the citations between them, but they differ in coverage philosophy, the headline metrics they publish, and how each is used in research assessment.

    This article compares the two systems across the dimensions that matter for choosing and interpreting them, and offers a side-by-side table to summarise the differences.

    Coverage and selection

    Both databases are curated rather than exhaustive, applying editorial selection to the titles they index, but they make different trade-offs. Scopus is generally regarded as having a broader title list and wider coverage of disciplines, regions and document types, while Web of Science’s Core Collection is associated with a more tightly selective tradition rooted in the citation-index approach pioneered by Eugene Garfield. Neither covers the entire scholarly literature, and any analysis drawn from them is shaped by what each chooses to index. We unpack the Web of Science side in detail in our Web of Science explainer.

    The headline metrics: CiteScore and the Impact Factor

    Each platform has its own flagship journal-level metric. Scopus publishes CiteScore, a citation-per-document measure computed over a multi-year window from Scopus data. Web of Science, through the Journal Citation Reports, publishes the Journal Impact Factor, computed over a shorter window from Web of Science data. Because the two metrics use different source databases and calculation windows, a journal’s CiteScore and Impact Factor are not directly comparable, and a title may rank differently depending on which system you consult.

    Both are journal-level indicators. Neither is a reliable measure of the quality of an individual article or researcher, and responsible-metrics frameworks consistently warn against that misuse.

    Side-by-side comparison

    Dimension Scopus Web of Science
    Provider Elsevier Clarivate
    Type Abstract & citation database Citation-index platform (Core Collection)
    Coverage style Broad, multidisciplinary selection Selective Core Collection
    Headline journal metric CiteScore Journal Impact Factor (via JCR)
    Metric source data Scopus citations Web of Science citations
    Access Subscription Subscription

    Use in research assessment

    Both databases are widely used in research evaluation, university rankings and bibliometric studies, and many institutions subscribe to both because their differing coverage produces different — and complementary — views of the same literature. A bibliometric analysis can yield materially different results depending on which database supplies the underlying data, so methodological transparency about the source is essential.

    Crucially, citation databases describe attention and connectivity, not intrinsic merit. Movements such as responsible-metrics and narrative-CV approaches encourage assessors to use these tools as one input among many, alongside qualitative judgement and contributor-level information such as that captured by the CRediT contributor-roles taxonomy. Both systems also depend on persistent identifiers — especially the DOI — to disambiguate and link records accurately, and they sit within the broader landscape of research information systems.

    Which should you use?

    There is no universally correct answer. For the widest net across disciplines and document types, Scopus is often preferred; for the longer-established citation-index tradition and the Journal Impact Factor specifically, Web of Science is the source. For any serious analysis, using both and being explicit about coverage limitations is the most defensible approach. Definitions of the metrics named here are maintained in the CASRAI dictionary.

    Frequently asked questions

    Is Scopus bigger than Web of Science?

    Scopus is generally described as having a broader title list and wider document coverage, while Web of Science’s Core Collection is more selective. The right database depends on whether breadth or selectivity matters more for your purpose.

    Can I compare a CiteScore directly with an Impact Factor?

    No. CiteScore and the Journal Impact Factor are computed from different source databases over different time windows, so the two numbers are not interchangeable and should not be compared head to head.

    Do universities subscribe to both?

    Many research institutions subscribe to both Scopus and Web of Science precisely because their differing coverage gives complementary perspectives on the literature and on journal performance.

    Are these databases suitable for evaluating individual researchers?

    Their journal-level metrics are not designed to assess individuals, and responsible-metrics guidance cautions strongly against using them that way. They are best treated as one input within a broader, qualitative assessment.

  • CiteScore, SNIP and SJR: Journal Metrics Compared

    CiteScore, SNIP and SJR are three journal-level metrics, derived from the Scopus database, that describe a journal’s citation profile in complementary ways. CiteScore offers a straightforward average of citations per document, SNIP corrects for differences in citation behaviour between fields, and SJR weights citations by the prestige of the citing source — together giving a fuller picture than any single number.

    All three respond to a recurring problem: raw citation counts are easy to misread. They differ by discipline, are inflated by self-citation and concentrate around a few highly cited papers. The metrics below each address part of that problem, but none should be treated as a measure of an individual article or author — a principle central to DORA and responsible assessment.

    How the three metrics differ

    Metric Source Core idea What it adds
    CiteScore Scopus Citations per document over a multi-year window Transparent, broad coverage, easy to interpret
    SNIP Scopus / CWTS Source-normalised impact per paper Corrects for differing citation density between fields
    SJR Scopus Prestige-weighted citations (eigenvector logic) Values citations from influential journals more highly

    CiteScore

    CiteScore divides the citations a journal receives over a defined multi-year window by the documents it published in that window. Its appeal is transparency and breadth: it is calculated consistently across the whole Scopus catalogue and is simple to interpret. Because the underlying calculation is openly described and the numerator and denominator are defined the same way, the figure is reproducible and comparatively hard to dispute. Its limitation is that, like any raw average, it does not account for the fact that some fields simply cite more than others, nor for the heavy skew in how citations distribute within a single journal.

    SNIP — source-normalised impact per paper

    SNIP, developed at CWTS in Leiden, addresses exactly that field-difference problem. It normalises a journal’s citations against the citation potential of its subject area — how often papers in that field tend to cite at all. The effect is to make a journal in a sparsely cited field comparable to one in a densely cited field, so cross-disciplinary comparison becomes more meaningful.

    SJR — Scimago Journal Rank

    SJR takes a different angle, weighting citations by the prestige of the citing journal using an eigenvector approach related to the logic behind the Eigenfactor and altmetrics. A citation from a highly regarded, frequently cited journal contributes more than one from an obscure source. SJR therefore captures something closer to influence within a citation network than a simple count can.

    How these metrics relate to the Impact Factor

    The traditional Journal Impact Factor, drawn from a different database, is essentially a two-year average of citations per citable item — conceptually closest to CiteScore, though calculated over a shorter and differently defined window. CiteScore, SNIP and SJR were each designed to address a weakness of that older measure. CiteScore widens coverage and uses a longer window; SNIP adds the field normalisation the Impact Factor lacks; and SJR replaces flat counting with prestige weighting. Understanding these lineages helps explain why a journal can rank differently on each metric: they are not measuring the same thing, and a journal strong on raw volume may look more modest once citations are normalised by field or weighted by source. The full critique of the older measure is set out in our piece on the journal impact factor, and the broader question of how to read these indicators sensibly runs through our coverage of responsible research assessment. Treating any of them as interchangeable, or as a single league table, is the mistake responsible-assessment frameworks were written to prevent.

    Why field normalisation matters

    The single most consequential difference between these metrics is whether they correct for discipline. Citation cultures vary enormously: a molecular biology journal and a pure mathematics journal can have wildly different baseline citation rates simply because of how often, and how quickly, their fields cite. A raw average such as CiteScore will make the biology journal look more impactful even if both are equally central to their fields. SNIP exists to neutralise that distortion by benchmarking against each field’s citation potential, which is why it is the most defensible choice for comparing journals across disciplines. SJR addresses a different axis — not how many citations, but how prestigious their sources are.

    Choosing the right metric for the question

    No single metric is “best”; each answers a different question. The table below maps common questions to the most informative indicator.

    Your question Most informative metric Why
    How much is this journal cited overall? CiteScore Transparent raw average
    How does it compare across fields? SNIP Corrects for citation density
    How prestigious are its citing sources? SJR Weights citations by source standing
    Is this paper or author any good? None Read the work; use peer judgement

    Common misuses to avoid

    The most frequent error is transferring a journal-level number onto an individual paper, researcher or grant application. Because citations within a journal are concentrated in a minority of articles, a high journal metric says almost nothing about a randomly chosen paper it contains. A second misuse is comparing across fields with an un-normalised metric, and a third is treating any of these indicators as a measure of quality rather than of citation behaviour. A fourth, subtler error is using one year’s figure as if it were stable, when journal metrics fluctuate from year to year for reasons unrelated to quality. Each is explicitly cautioned against by responsible-assessment frameworks, which recommend reporting a range of indicators with their definitions rather than a single decontextualised number.

    Using metrics responsibly

    These indicators describe journals, not the work inside them. The distribution of citations within any journal is highly skewed, so a journal’s metric tells you little about a specific paper. Responsible-assessment principles — set out in our coverage of responsible assessment and grounded in the critique of the journal impact factor — recommend judging research on its own merits, using metrics only as context and never as a proxy for quality. The wider toolkit, including network-weighted and attention indicators, is covered in our guide to standardised terminology and our overview of the Eigenfactor and altmetrics. Authors documenting their contributions can consult our guidance for authors.

    Frequently asked questions

    What does CiteScore measure?

    CiteScore measures the average number of citations received per document a journal published over a defined multi-year window, calculated consistently across the Scopus database.

    Why is SNIP useful for cross-field comparison?

    SNIP normalises citations against the citation potential of a journal’s field, so journals in disciplines that cite sparingly are not unfairly penalised against those in heavily citing fields.

    How is SJR different from CiteScore?

    CiteScore treats all citations equally, whereas SJR weights them by the prestige of the citing journal, capturing influence within the citation network rather than a flat count.

    Can these metrics evaluate an individual paper or researcher?

    No. They are journal-level indicators. Citation distributions within journals are highly skewed, so under DORA they should not be used to judge individual articles or people.