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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

The digital science company Altmetric has developed the "doughnut" symbol as a way of visualising the reach and impact of an article. It can be attached to an article, dataset or other research object online. The score in the centre of the doughnut is based on:

  • how many people share or mention the article
  • where they mention it (for example, newspapers give a higher score than tweets)
  • who is talking about it (the media, the public or other researchers).

The colours reflect the mix of sources, which might include Facebook, Twitter, news outlets, government policy documents, or blogs (among others).

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:

  • Instal the free Altmetric browser bookmark to display any altmetrics for articles you read online.
  • 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 linking it to your research outputs online.
  • Track analytics for your papers on Academia.edu, including common search terms and countries of your readers.

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.

Different altmetric tools evaluate different sources, so an article may appear to be very popular according to one tool, but less popular according to another.