Altmetric supports the use of its data in the development of journal-level indicators and metrics that adhere to “responsible metrics” practices, especially when such metrics are used as part of a multi-indicator or “basket of metrics” approach to understand journal-level influence. 


In general, Altmetric supports the development of journal-level indicators and metrics that:

  • Account for known skew using coverage percentiles (e.g. “% articles with an Attention Score in a journal”), geometric means, or medians (technically allowed, but discouraged).

  • Address biases related to subject area, location, and other confounding variables, for example by using subject-area normalization.

  • Look beyond the boundaries of specific journals towards network analysis, communications theory, and topic-based analysis.

  • Are transparent and otherwise in line “responsible metrics” practices described by the Leiden Manifesto.


We encourage that researchers think carefully about using the correct denominator in developing their journal-level metrics. Altmetric data typically does not include the entirety of all articles published by a journal; instead, we index only those articles that have been mentioned in a source we track (with a few exceptions). It’s better to use an independent source (e.g. Dimensions, Scopus, Web of Science) that provides reliable and auditable data to determine a reputable denominator.


Analysts should avoid using basic calculations like sums or averages based upon the Altmetric Attention Score or source-specific counts (e.g. number of tweets). These metrics do not account for the relatively large amount of outliers that exist in any given sample.