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Measuring research impact

What are altmetrics?

Altmetrics are based on the number of times an article is shared, downloaded or mentioned on social media, blogs or in newspapers.

You should consider Altmetrics alongside traditional bibliometric measures such as citation counts, h-index or journal impact factors. This will give a wider picture of how a piece of research is being read and discussed. Altmetrics also give a more immediate indication of how an article is received than citations in publications.

The Altmetric doughnut

Altmetric developed the doughnut symbol as a way of visualising the attention a research output has received. It can be attached to an article, dataset or other research object online.

The Altmetric Attention Score in the centre of the doughnut is a count of all of the attention a research output has received in sources such as social media, blogs, newspapers and course syllabus. Each source is weighted by the company. For example, newspaper reports get a higher score than tweets.

The colours in the doughnut reflect the mix of sources. Take a look at this Almetric example article to see how the score is calculated.

The Altmetric doughnut tool works best with articles published after July 2011, and may underestimate scores for older articles.

How can I find altmetric data?

Ways to find altmetric data:

  • Install the free Altmetric bookmark to display altmetrics for any published research output with a DOI.
  • Use Figshare – an online repository for research outputs including posters, slideshows, and datasets – to see how many shares and citations an output has had.
  • Create a personal profile on ImpactStory and link it to your research outputs online.

What are the limitations of altmetrics?

Like any other metrics, altmetrics have their limitations.

A high number of shares or social media mentions does not necessarily mean that an article is of high quality. An article may be mentioned on social media because it contains something amusing or unusual.

Social media can also be easily manipulated and "likes" or mentions can be paid for or generated, so the numbers might not reflect the actual level of public interest in a piece of work.