In today’s fast-paced digital world, measuring the impact of research extends far beyond traditional citations. You may have encountered a colorful donut graphic accompanied by a central number while exploring research articles online. This is the Altmetric “donut,” and the number is the Altmetric Attention Score. This metric offers a valuable insight into the web-driven scholarly interactions surrounding a research output, providing a complementary perspective to conventional citation-based metrics. It allows researchers and others to carefully track where articles are being shared and discussed across a broader spectrum of online sources.
Selecting the Altmetric icon near an article title unveils detailed information, including title, journal, publication date, DOI, and author details. The donut itself, prominently displayed on the article metrics page, is not just a visual element; it’s a representation of the attention the research has garnered. Beneath the donut, a question mark icon provides a crucial pop-up definition: “The Altmetric Attention Score for a research output provides an indicator of the amount of attention that it has received.” This score, derived from an automated algorithm, is a weighted count of the mentions a research output receives from various online sources. To truly understand its value, it’s essential to delve deeper into how this score is calculated and what it signifies.
The Altmetric score is not a simple tally; it’s a nuanced metric calculated using three primary factors: volume, sources, and authors. Volume refers to the number of times an article is mentioned. However, to prevent score inflation, only one mention per person per source is counted. If someone tweets about the same paper multiple times, only the first tweet contributes to the score. Sources are categorized, and each category carries a different base weight. For instance, a mention in a mainstream media news outlet contributes more significantly to the score than a blog post, which in turn contributes more than a tweet. Finally, the author factor considers the influence and context of the mention. Altmetric scans the author of each mention, assessing their scholarly activity, potential biases, and audience. A researcher sharing a link with fellow researchers holds more weight than an automated journal account posting the same link.
| Source name | Collection method | Update frequency | Notes |
|---|---|---|---|
| Third party data provider API | Real-time feed | An online news and social networking service where users post and interact with messages, called “tweets.” | |
| Facebook API | Daily | An American for-profit corporation and an online social media and social networking service. | |
| Policy Documents | PDFs collected and scanned from policy sources and repositories | Daily | Scanning and text-mining international policy document PDFs for references, which are looked up in CrossRef/PubMed and resolved to DOIs. |
| News | RSS feeds and API | Real-time feed | Manually curated news sources, with data provided via a third-party provider and RSS feeds direct. |
| Blogs | RSS feeds | Daily | A discussion or informational website published on the World Wide Web consisting of discrete, often informal diary-style text entries. |
| Mendeley | Mendeley API | Daily | A desktop and web program produced by Elsevier for managing and sharing research papers, discovering research data and collaborating online. |
| Scopus | Scopus API | Real-time feed | Elsevier’s abstract and citation database. |
| Post-publication peer reviews | PubPeer and Publons APIs | Daily | Peer review comments collected from item records and associated by unique identifier. |
| Reddit API | Daily | An American social news aggregation, web content rating, and discussion website. Registered members submit content to the site such as links, text posts, and images, which are then voted up or down by other members. | |
| Wikipedia | Wikipedia API | Real-time feed | Mentions of scholarly outputs collected from References section. English Wikipedia only. |
| Stack Overflow Q&A | Stack Overflow API | Daily | A privately held website created in 2008 to be a more open alternative to earlier Q&A sites. A platform for users to ask and answer questions. |
| F1000 Reviews | F1000 API | Daily | Faculty of 1000 Research is an open research publishing platform that offers immediate publication of articles and other research outputs without “editorial bias.” Includes transparent peer review and inclusion of all source data. |
| Google+ | Google+ API | Daily | An internet based social network. Public posts only. |
| YouTube | YouTube API | Daily | An American video-sharing website. Scans for links to scholarly outputs in video comments. |
| Open Syllabus | Static Import from Open Syllabus | Quarterly | Academic data mining project based at Columbia University that analyzes over 1 million college course syllabi. |
| Web of Science | Clarivate Analytics API | Real-time feed | Citation counts from peer-reviewed literature. |
The colors within the Altmetric donut visually represent the sources of attention. Medium blue indicates mentions on LinkedIn, yellow signifies blog mentions, red denotes mainstream media sources, and purple represents policy documents, among others. The proportion of each color varies depending on the sources where the research has received attention. Because many of these sources provide real-time or daily updates, both the donut’s colors and the score itself can fluctuate daily, reflecting the dynamic nature of online engagement.
| Volume | Sources | Authors |
|---|---|---|
| The score for an article rises as more people mention it. Only 1 mention from each person per source is counted. If someone tweets about the same paper more than once, Altmetric will ignore all but the first. | Each category of mention contributes a different base amount to the final score. For example, a newspaper article contributes more than a blog post, which contributes more than a tweet. | Altmetric looks at how often the author of each mention talks about scholarly articles, at whether or not there’s any bias towards a particular journal or publisher and at who the audience is. For example, a researcher sharing a link with other researcher counts for more than a journal account pushing the same link out automatically. |
Beyond the donut and score, the article metrics website provides further contextual information. Selecting “more…” reveals percentile rankings among all research outputs scored by Altmetric, rankings within the same source, comparisons to outputs of similar age, and percentiles within outputs of similar age and source. It also details where the article has been mentioned (e.g., news, blogs) and reader counts on platforms like Mendeley. Tabs at the top offer source-specific breakdowns (Twitter, Facebook, Wikipedia, etc.), while sections at the bottom delve into Twitter Demographics, Mendeley Readers, and Attention Score in Context, providing deeper insights into readership statistics and comparative attention levels.
The Altmetric Attention Score offers several advantages. It provides immediate insights into an article’s reach and influence, unlike citation metrics that can take considerable time to accrue. It also tracks how attention evolves over time, allowing researchers to monitor the ongoing engagement with their work. Furthermore, it captures a broader spectrum of impact by considering diverse online sources, including social media, news outlets, policy documents, and blogs, offering a more holistic view than citation counts alone.
However, it’s crucial to interpret the Altmetric score with care. The score reflects attention, not necessarily quality. An article might receive a high score due to controversy or negative feedback. Social media mentions, while valuable for gauging early reactions and broader impact, may not always correlate directly with the scholarly value of a research paper. Journal variation is another factor; a “good” score in one journal might be considered low in another with a wider readership, such as Science or Nature.
It’s also important to note that Altmetric data collection began in mid-2011, so older articles may have limited or no scores unless they’ve garnered recent attention. Scores typically increase over time but can decrease if online mentions are removed. Therefore, when using and interpreting the Altmetric score, context is key. It should be used as one piece of the puzzle, alongside traditional metrics like impact factor, H-index, downloads, and citation counts, to provide a more comprehensive understanding of a research article’s overall impact. The Altmetric Attention Score, when understood and applied thoughtfully, offers a valuable, real-time perspective on the broader influence and reach of scholarly work in the digital age.
