Output metrics consist of two types:

• Citation-based metrics, based on the number of times an output is cited, generally by other academic sources
• Alternative metrics, which include online citations to digital research or policy documents and usage-based indicators, such as views, downloads, comments, bookmarks, or mentions on social media.

The information on this page focuses on citation-based metrics; please visit our companion page for information on alternative metrics.

The simplest citation-based output metric is citation count, a measure of the number of citations an output has received. Citation counts can be found in many citation databases including Scopus, Web of Science and Google Scholar. Citation counts are easy to quantify but have a number of significant limitations:

• They are not comparable across disciplines where citations accumulate at different rates
• They do not take account of the age of an output - in many disciplines it takes time for citations to accrue
• They do not take account of the type of publication - different output types attract varying numbers of citations and accrue citations at different rates.

Field-weighted citation impact

Field-weighted citation impact (FWCI) is the ratio of the total citations received by an output, and the total citations that would be expected based on the average for that field. Field-weighted citation impact can be found in Scopus.

An FWCI of:

• Exactly 1 means that the output performs just as expected for the global average.
• Greater than 1 means that the output is more cited than expected according to the global average. For example, 1.48 means 48% more cited than expected.
• Less than 1 means that the output is cited less than expected according to the global average.

FWCI takes into account the differences in research behaviour across disciplines. It is particularly useful for interdisciplinary outputs although it can be applied to any output. The expected total citation count is calculated based on year of publication, subject field and output type. The FWCI can therefore be used to compare outputs of different types and age, and across different disciplines.

Using citation-based output metrics responsibly

• Ensure you have curated your online profile on the database you are going to use – Scopus, Web of Science or Google Scholar.
• Check metrics on each of the databases to see which gives you the highest score. Varying coverage of citation indexes means these metrics can differ significantly from one bibliometric database to another. Coverage of monographs, chapters and non-English language outputs are poorly represented in some databases. State the source you used and the date it was calculated so that it can be replicated and/or defended if necessary.
• Include other data. Don’t just rely on one measure to encapsulate the impact or reach of an output. Include contextual information, for example alternative metrics, information about your contribution to the research, or data about how the research has been used or applied.
• Challenge the use of these metrics and understand their limitations.