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Altmetrics: Altmetrics

What are altmetrics?

Altmetrics are metrics and qualitative data that are complementary to traditional, citation-based metrics. 

They can be metrics based on online activity, mined or gathered from online tools and social media for example:

  • tweets, mentions, shares or links
  • downloads, clicks or views
  • saves, bookmarks, favourites, likes or upvotes
  • reviews, comments, ratings or recommendations
  • adaptations or derivative works
  • readers, subscribers, watchers or followers

Examples include (integrated into University of Southampton Institutional Repository ePrints Soton) and PlumX (integrated with Pure)


Metrics for alternative research outputs, for example citations to datasets and theses

Downloadable guide -  guide to Altmetrics.

Responsible Use

Altmetrics should only be used as a guide for how much attention a research output is receiving relative to similarly aged outputs; High scores are indicative of high engagement, but altmetrics cannot tell the difference between negative and positive cites.

For example, ‘Experimental replication shows knives manufactured from frozen human feces do not work’ which as of September 2021 has been tweeted, shared, and liked over 21000 times, many came from the humour value or for derision that the topic would count as ‘science’. However, the level of engagement the article generated led to it winning the 2020 Ig-Nobel award for Materials Science



Speed  Can accumulate more quickly than traditonal metrics Standards  There are no standards or regulations for altmetrics
Range  Covers many types of research output, not just articles Overload  There is no single widely used rating or score, as there are many different metrics and providers it can be hard to determine which are relevant
Detail  Can give a fuller picture of research impact Reliability  Measures popularity rather than quality and is not able to tell the difference between negative and positive cites
Granularity  Can provide metrics at the article, rather than journal, level

Difficulty  Can be difficult to collect, for example bloggers or tweeters may not use unique identifiers for articles

Inclusive  Measures research activity outside of academia Acceptance Not used by many funders and institutions
Sharing  If researchers get credit for a wider range of research outputs it could motivate further sharing Context  Use of online tools may differ by discipline, geographic region, and over time, make almetrics difficult to interpret