Altmetrics are indicators of the online attention research attracts — mentions, shares, saves and references across the web and social platforms — while the Eigenfactor and its companion Article Influence score weight citations by the standing of the journals that make them. Together they extend evaluation beyond the traditional impact factor, but they measure attention and influence, not the intrinsic quality of any single study.
Both families of indicator emerged from dissatisfaction with a single citation average. The Eigenfactor refines the citation signal itself; altmetrics capture engagement that citations miss entirely. Neither replaces careful reading, and both invite misinterpretation if treated as scores of merit. They are best thought of as additional lenses on a body of work, each illuminating something a single citation count obscures, rather than as rival verdicts competing to crown a winner.
The Eigenfactor and Article Influence score
The Eigenfactor score treats the scholarly literature as a network and ranks journals by the influence of the citations they receive, using an eigenvector method conceptually similar to how web pages are ranked by the importance of the pages linking to them. A citation from a heavily cited, influential journal counts for more than one from a peripheral source. Because the raw Eigenfactor scales with journal size, the Article Influence score normalises it per article, giving a per-paper measure of average influence that is comparable across journals of different sizes. A further refinement is that author self-citations between journals are typically discounted, so a journal cannot inflate its standing simply by citing itself. This network logic is shared with the prestige-weighted journal metrics covered in our guide to CiteScore, SNIP and SJR.
Why network weighting changes the picture
Network weighting matters because not all citations are equal. A flat count treats a citation from a marginal, rarely read journal exactly the same as one from a central, heavily cited venue, yet the two clearly carry different evidential weight. The eigenvector approach behind the Eigenfactor and the Article Influence score captures this by letting influence flow through the citation network: a journal cited by influential journals inherits some of that influence, recursively. The effect is to surface journals that are central to the scholarly conversation rather than merely voluminous. It also dampens the impact of citation farming and self-citation, because citations from low-influence sources contribute little. This is the same insight that powers the prestige-weighted journal metrics, and it is one reason network measures are harder to game than raw counts.
What altmetrics measure
Altmetrics aggregate diverse online signals: news coverage, policy-document references, social-media mentions, reference-manager saves and blog discussion. Their strengths are speed and breadth — attention accrues within days, long before citations appear, and captures reach into audiences such as practitioners, policymakers and the public that citation counts overlook. A paper influencing clinical guidance or public debate may register strongly in altmetrics while accumulating citations slowly. This timeliness makes altmetrics valuable for spotting emerging work and for evidencing societal reach in ways the slow accrual of citations cannot, particularly for research whose primary audience lies outside academia.
The risk of gaming and manipulation
Every metric that carries reward eventually attracts manipulation, and attention-based measures are especially vulnerable. Social-media mentions can be inflated by coordinated promotion, and raw counts can be padded by automated accounts, so a high altmetric score is not by itself evidence of genuine influence. Network-weighted citation measures are more robust, because influence must be conferred by sources that are themselves influential, but they are not immune to citation rings. The practical defence is the same in both cases: never treat a single number as decisive, look at the underlying sources, and combine quantitative signals with expert judgement of the work itself.
What altmetric signals do and do not capture
It helps to be precise about which signals carry which meaning. Some altmetric sources hint at scholarly or societal influence; others are pure visibility. The table below sketches the spectrum.
| Signal | What it suggests | How to read it |
|---|---|---|
| Policy-document citations | Uptake into practice or governance | Strong societal-impact hint |
| Reference-manager saves | Scholarly interest from researchers | Early engagement signal |
| News coverage | Public salience | Reach, not validity |
| Social-media mentions | Topical attention | Volatile; controversy-prone |
Attention is not impact
The central caution is that online attention and scholarly impact are different things. A paper can be widely shared because it is controversial, surprising or even flawed; volume of mentions says nothing about validity. Altmetrics are best read as a measure of reach and engagement, complementary to citations rather than a substitute. Conflating the two risks rewarding visibility over rigour, and can even create perverse incentives to court attention rather than do careful work. Authors evidencing the reach of their own work — for example in narrative impact statements — can find guidance in our resources for authors, which encourage describing influence in context rather than leaning on a single attention score.
Where these metrics complement citation counts
Used well, the Eigenfactor family and altmetrics fill different gaps left by a simple citation average. The Eigenfactor refines the citation signal itself, distinguishing influential citations from peripheral ones — a logic it shares with the prestige-weighted journal indicators in our guide to CiteScore, SNIP and SJR. Altmetrics, by contrast, capture timely engagement and societal reach that citations record only slowly, if at all. The two are most useful in combination: citations for scholarly influence over time, altmetrics for early and broader attention, neither standing in for a reading of the work.
Reading these indicators responsibly
Both the Eigenfactor family and altmetrics should be interpreted within a responsible-assessment framework. The principles of DORA and responsible research assessment, alongside the Leiden Manifesto, stress quantitative indicators as support for — not a replacement of — expert judgement, transparency about what each metric does and does not capture, and avoidance of single-number rankings of people. The longstanding critique of the journal impact factor applies equally here: an indicator’s value depends entirely on using it for the question it can actually answer. Our broader coverage of responsible assessment sets out how these tools fit together.
Frequently asked questions
What does the Eigenfactor add over a citation count?
It weights citations by the influence of the citing journal, so a citation from a highly cited source counts for more, capturing standing within the citation network rather than a flat tally.
Why normalise to the Article Influence score?
The raw Eigenfactor grows with journal size. Dividing by the number of articles yields a per-paper average influence that can be compared fairly across large and small journals.
Do altmetrics show that research is good?
No. Altmetrics show attention and engagement, not quality. A paper may attract mentions because it is controversial or flawed, so altmetrics complement rather than replace careful evaluation.
How should these metrics be used responsibly?
Use them as context alongside expert judgement, be transparent about what each measures, and avoid reducing researchers or papers to a single number — the core of DORA and the Leiden Manifesto.
