Altmetrics monitors the visibility of publications, such as articles and books, on social media and other online services. It combines data such as download numbers of publications, mentions about them on news sites, tweets, reactions and traditional citations.

Compared to traditional citations, altmetrics help identify the impact of publications faster. Tweets on Twitter and mentions on news outlets may accumulate very quickly after publishing the publication compared to citations, which take months and even years to accumulate.

Publications need to have an established permanent identifier to be noted in altmetrics calculations. Such identifiers include, for example:

• DOI: usually for articles published in various publication channels, but also datasets, among others.
• ISBN: for books
• URN: several publication types

A publication with a persistent identifier should be displayed on a service that is tracked by altmetrics tools. The most common sources monitored by altmetrics services are Twitter and Facebook. The background sources monitored by the services vary.

Altmetric Explorer

The most visible altmetrics service is Altmetric Explorer. It can usually be identified by the colourful donut symbol or the icon with Altmetric text. The service is already used by many international publications, which present the attention score calculated by the Altmetric Explorer service alongside their articles. Example of the information provided by the service.

The altmetrics donut depicts the attention of a publication in two ways:

• The number in the middle of the donut is a numeral indicator of the attention: the higher the number, the better the attention score it has been assessed to have. This value is based on the publication’s visibility in various online services, and some of the services are emphasised over others. For example, a mention of a publication on a news site has eight times the weighted value of one tweet posted to Twitter.
• The different colours of the donut demonstrate the percentages of different online services in the publication’s visibility. For example, if most of the donut has a light blue colour, this signifies that the publication has its attention from Twitter.

Find out more about the meaning of donut colours and the calculation principles of the attention scores as well as sources of attention.

There are a few free options of the service. The service allows users to, for example, download a bookmark for their browser (browser plugin), which shows data about a publication with a DOI through the Altmetrics donut. It is also possible to get a free basic version of the service requiring registration for two users per organisation.

The paid Altmetric Explorer for Institutions allows for organisation-specific reviews by adding the organisation’s structure, such as faculties and units, into the service. The service also allows for saving searches, creating reports and transferring data to Excel, among other options.

PlumX

PlumX works quite similarly to the better-known Altmetric Explorer. In the PlumX calculation, a publication is not assigned an individual value.

• The PlumX icon uses colours to indicate in which categories the publication has gained attention. The service applies five categories. 
• The size of the ‘branches’ demonstrates the level of visibility in the different online services. For example, if a blue branch is larger than the others, this signifies that the publication has gained a great deal of visibility on social media.

Read more about the PlumX metrics and their colour codes on the service’s own website. 

Many databases and websites of journals have integrated the PlumX Metrics into their platforms to provide users with article-level altmetric data. Some popular platforms utilising PlumX Metrics are: Scopus, ScienceDirect and Mendeley. In some cases, it is possible to download the PlumX icon for free for non-commercial open access journals and open access repositories. 

A paid PlumX Dashboard allows the user to review organisation-level results based on a researcher, topic, journal, degree programme and department.

CrossRef Event Data

CrossRef Event Data monitors the visibility of publications and uses DOI to gather information about publication-related events happening online, such as mentions in news articles or in social media. The event consists of three parts: the subject, i.e. where the research was mentioned (such as Wikipedia), the object, i.e. which research was mentioned based on the DOI information, and the relationship, i.e. how the research was mentioned (such as citations or discussions). CrossRef Event Data data are available via a public free API. Data sources used are e.g., news sites, blogs and social media. The service tries to monitor as many online events as possible, but there are limitations in its coverage.

Notes regarding altmetrics

The advantages of altmetrics compared to traditional methods of publication metrics:

• Citations and altmetric results have a weak correlation as they measure different types of use of the publications (reactions, sharing and downloads).
• Altmetrics can identify the attention gained by publications faster, as online discussions are often more immediate.
• Altmetrics reach different user communities (including users outside the scientific community) and reflect the different impacts created by research (social impact).
• Data produced by altmetrics is easily available, in principle.

Challenges of altmetrics:

• So little data is usually accumulated that statistical analysis is not reasonable.
• Social media indicators are heterogenous, which means that interpreting the meaning of discussions, mentions, shares and comments is challenging.
• Ease of use (easy to react, share, etc.), which increases the risk of skewed results (for example by liking something as a joke).
• Does the indicator reflect a passing interest or a actual impact?
• Differences between fields of science (medical, biosciences, social sciences and humanities get more hits than technology and natural sciences).
• Manipulation of results (related to the built-in operating principle of social media)
• Lifecycle effect of the channels monitored (e.g. the significance of certain channels diminishes, monitoring of a channel ends or new channels to follow are added to the service).

Read more

Fraumann, G. (2020) What lies behind altmetrics scores? Guidelines on how to use qualitative approaches in altmetrics. A report from LIBER’s Innovative Metrics Working Group. LIBER. Available: https://libereurope.eu/wp-content/uploads/2020/12/Guidelines-on-how-to-use-qualitative-approaches-in-altmetrics-1.pdf 

Avoin tiede ja tutkimus -hanke, Vaikuttavuusselvitys -työryhmä (2015) ATT-vaikuttavuusselvitysryhmän raportti: Selvitys. Available: https://urn.fi/URN:NBN:fi-fe2016122731715