Metrics are embedded throughout Scopus at the journal, article and author levels. All of these metrics are designed to help facilitate the evaluation of authors, journals and articles. These metrics also provide enhanced views of research areas and help build valuable insights.
Document-level metrics quantify the reach and impact of published research. Scopus integrates data from PlumX Metrics as the primary source of its article-level metrics, along with traditional measures (such as citations) to present a richer and more comprehensive picture of an individual article’s impact.
With Scopus document metrics, you can:
PlumX Metrics provide insights into the ways people interact online with individual pieces of research output (such as articles, conference proceedings, book chapters and others). To support like-with-like analysis and help make sense of the huge amounts of data involved, PlumX Metrics are divided into five categories:
Citations: This category contains both traditional citation indexes, such as Scopus, as well as citations that help indicate societal impact, such as clinical, patent or policy citations.
Usage: This indicates how often people are reading an article or otherwise using the research. After citations, usage is the statistic that most interests researchers.
Captures: A capture indicates that someone wants to come back to the work — and it can be a leading indicator of future citations.
Mentions: This measures activity such as news articles or blog posts about research. It’s a way to tell that people are truly engaging with the research.
Social media: This category includes tweets, Facebook “likes” and other social media posts that reference the research. Social media can help measure buzz and attention. Social media can also be a good measure of how well a particular piece of research has been promoted.
Plum Print: For quick and easy comprehension, these five categories of metrics are also displayed as a data visualization known as the Plum Print. Each colored circle in the Plum Print represents the metrics in the associated category. The larger the circle, the more metrics in that category.
Note: The five categories are represented separately because each one represents a different type of engagement and should not be combined into a single score.
Beside PlumX Metrics, these additional document metrics are also available in Scopus:
FWCI (field-weighted citation impact) considers variations in research and citation behavior across disciplines and facilitates benchmarking among disciplines.
It is the number of citations received by a document divided by the expected number of citations for similar documents in the same field of research.
Citation benchmarking calculates how citations for this article compare with the average for similar articles in the same field.
Journal-level metrics on Scopus include:
Each journal overview page contains these details:
CiteScore Tracker (monthly update)
CiteScore Rank and Trend
CiteScore is a family of eight indicators that offer complementary views to analyze the publication influence of serial titles of interest. Derived from the Scopus database, CiteScore metrics offer a more transparent, current, comprehensive and accurate indication of a serial’s impact. CiteScore metrics are available for all active journals (25,300 per June 2020; 13,000 more than Journal Impact Factor).
As of June 2020 the definition of CiteScore has changed, now only including typically peer-reviewed research: articles, reviews, conference papers, data papers and book chapters, covering 4 years of citations and publications. Historical data back to CiteScore 2011 have been recalculated and are displayed on Scopus.
SNIP (Source Normalized Impact per Paper) Measures contextual citation impact by weighting citations based on the total number of citations in a subject field. The impact of a single citation is given higher value in subject areas where citations are less likely, and vice versa.
SJR (SCImago Journal Rank): Based on the concept of a transfer of prestige between journals via their citation links. Drawing on a similar approach to the Google PageRank algorithm - which assumes that important websites are linked to from other important websites - SJR weights each incoming citation to a journal by the SJR of the citing journal, with a citation from a high-SJR source counting for more than a citation from a low-SJR source. The calculation of the final SJR of a journal is a complex and iterative process.
Compare up to 10 sources and review results on a chart or in table format
Search for sources to compare by title, ISSN, publisher, subject area
Compare CiteScore for each publication by year
Compare SNIP for each publication by year
Compare SJR for each publication by year
Compare number of documents for each publication by year
Compare percent of articles cited for each publication by year
Compare percent of review articles published in each publication by year
Author metrics allow users to:
Available author metrics include:
Analyze author output: A collection of in-depth and visual analysis tools designed to provide a better picture of an individual’s publication history and influence