The statistical analysis of text-based research outputs (books, journal articles, conference papers, etc) with respect to citation counts. Based on how the citation details of outputs is utilised to analyse various aspects of research performance, most commonly used metrics can be classified into Author Level, Article Level and Journal Level.
There are various metrics that individual researchers can utilise to measure their research performance. Some of commonly used metrics include:
h-Index: The h-index is calculated by counting the number of publications for which an author has been cited by other authors at least that same number of times. For instance, an h-index of 17 means that the scientist has published at least 17 papers that have each been cited at least 17 times. If the scientist's 18th most cited publication was cited only 10 times, the h-index would remain at 17. If the scientist's 18th most cited publication was cited 18 or more times, the h-index would rise to 18.
g-index: A variant of the h-index that emphasises the most highly cited papers in a data set. The h-index does not give extra weighting to the most-cited publications of a data set that are likely the ones that are responsible for an entity’s prestige; g-index can be used if this feature of the h-index is seen as a weakness. The g-index is always the same as or higher than the h-index.
m-index: Another variant of the h-index that displays h-index per year since first publication. The h-index tends to increase with career length, and m-index can be used in situations where this is a shortcoming, such as comparing researchers within a field but with very different career lengths.
h5-index: This index uses a 5-year publication and citation window on the standard h-index calculation.
Learn more about using these indices in SciVal
I10-index: Introduced by Google Scholar, the i10-index measures the number of publications by an author with at least 10 citations.
Metrics that are used to measure the visibility of a researcher's work i.e. how often an output is cited in other publications.
FWCI: : SciVal’s field-weighted citation impact (FWCI) is an article-level metric that takes the form of a simple ratio: actual citations to a given output divided by the expected rate for outputs of similar age, subject and publication type. FWCI has the dual merits of simplicity and ease of interpretation: a value of 2 indicates that an output has achieved twice the expected impact relative to the world literature. It is a really useful addition to the benchmarking toolkit.
Citations per Publication - indicates the average citation impact of each of an entity’s publications: how many citations have this entity’s publications received on average?
Metrics that are used to measure the impact of a journal and compare their rankings against other journals
SJR: SCImago Journal Rank (SJR) is a metric based on the idea that ‘all citations are not created equal’. With SJR, the subject field, quality and reputation of the journal has a direct effect on the value of a citation.
SNIP: Source Normalized Impact per Paper (SNIP) 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.
Metrics that use alternative modes of measuring the visibility of a research output such as mentions on social media, news articles, policies and patents. Altmetrics gives a broader insight into how your research is being viewed and used beyond traditional citation metrics. This makes it useful for measuring new research outputs that are yet to receive citations in traditional scholarly publications. For further information on Altmetrics, refer to our libguide on Altmetric at Dundee: Who's talking about your research?
Altmetric monitors social media sites, blog posts, news stories, Wikipedia, Mendeley, Twitter, Facebook, government policy documents, patents and other sources for mentions of outputs.
PlumX is the second major aggregator of altmetrics.
It categorises metrics into five different categories.
