New metrics for new models of evaluation

Scholarly publishing has long relied on the expertise of editors and pre-publication closed peer review to determine the quality and significance of a research article, and in turn the overall content of a journal. How does the introduction of more granular metrics at the individual article level impact this approach, and what value do they add?


(This is a guest post by Cat Chimes of

In a post on this blog last week, Scott Epstein, Senior Product Manager at SpringerOpen, posed the question, “How do we evaluate the evaluators?” In his post, Scott suggested that article-level metrics, and altmetrics, place too much of a focus on the individual research output and therefore miss much of the comparison and contextual overview that a practiced journal editor accrues through experience.

While it is true that such metrics do provide an insight into the online activity surrounding a singular research output, what is not recognized in this is that it is those same metrics enable a broader comparison and evaluation on the part of not only the authors and readers of an article, but also the editors themselves—across content published in peer journals as well as their own.

Context, immediacy, and transparency: the value of altmetrics

Altmetrics (or alternative metrics) in particular offer a granular level of detail that readers and authors of articles would not have easily come across before. Beyond just counts of citations, downloads, and social media mentions, altmetrics (or certainly the data provided by, available across all Springer journal articles), provide much more immediate evidence of how an article has been received among both the general public and the wider academic community than download or citation counts alone are able to offer.

By detailing the original text of online references and mentions to a piece of research from sources such as public policy documents, Wikipedia, social platforms like Twitter and Facebook, mainstream news outlets, and online reference manager Mendeley, Altmetric data allows anyone reading the article to understand where the article has gained traction, and how it has been received.

As a number of publishers consider a move to open peer-review, sites such as Pubpeer and Publons provide a platform for academic comment—all of which is captured, collated and reported via Altmetric data. In some cases, such insight provides the opportunity to flag up background information that a reader of the article might otherwise be unaware of:

Sensitive Dogs 2

In addition, we’ve seen editors themselves making use of altmetrics data to inform strategic decisions. When determining potential changes of scope or selecting high profile articles for special additions, it can be particularly useful to be able to easily determine which publications have had the most resonance with readers.

Editorial Boards and publishers can also apply the data supplied by Altmetric to help, for example, identify desirable authors to invite to contribute to a specific title or future special issue. The Altmetric database contains attention data for close to 4 million individual research outputs, meaning that editors can browse, benchmark, and report on the online activity surrounding their own journals and articles with that of competing titles. Within this, they can see which authors in other journals are attracting a lot of attention for their work (and whether it is positive or negative), uncover emerging academic talents, and determine potential future peer-reviewers or board members.

Complementary to existing evaluation methods

Far from taking away from the evaluation and selection work done by journal editors, altmetrics and article level metrics simply offer another layer of context, further empowering the individual reader to come to their own conclusions about the quality of importance of a piece of research.

It cannot and should not be assumed that every article published in a journal with a high impact factor is of equal quality and importance, and having such insight at the individual article level allows for more vigorous review on the part of the reader as well as the editor.


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Seems like a great thing to add. It’s important to be able to evaluate things like this easily. Thanks for sharing these new metrics!

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