Demo corpus. Scores are computed on a select set of biomedical paper/datasets and may be inaccurate for papers outside this corpus — DataRank relies on network effects that improve with scale. We aim to expand this into a fully open resource pending additional funding.

Using Altmetrics to Support Research Evaluation

Communications in Computer and Information Science(2018)10.1007/978-981-13-1053-9_2Source: DataRank Database

Using Altmetrics to Support Research Evaluation is a research paper published in Communications in Computer and Information Science (2018). On theSindex it has a DataRank of 1.2. It has been cited 16 times, with 16 citing works in its 1-hop citation network.

N/A

1.2DataRank · unranked

1.2

16 citations · base score 2.8

Cite:

datarank_citation_only_1hop_v6· scope data_onlyMethodology

›Data sources & pipeline

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Pending

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (0/2)

Interoperable (0/2)

Reusable (0/3)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

Run a calibrated FAIR evaluation for this paper →

DataRank Breakdown

Base Score 35%Citation Network 65%

Base Score Contribution

0.425

From this paper's citation signal

Citation Network Contribution

0.792

From 14 citing papers with measurable signal

Learn more about DataRank methodology →

Top 5 citers driving the network score

Ranked by citation count — the same ordering the engine uses when summing log1p(C_q) over citers.

Bibliometrics: The Leiden Manifesto for research metrics
Nature20151,838 citationsDataRank 1.1
Do Altmetrics Work? Twitter and Ten Other Social Web Services
PLoS ONE2013907 citationsDataRank 1.0
Tweets as impact indicators: Examining the implications of automated “bot” accounts on <scp>T</scp>witter
Journal of the Association for Information Science and Technology2015208 citationsDataRank 10.4
Who reads research articles? An altmetrics analysis of <scp>M</scp>endeley user categories
Journal of the Association for Information Science and Technology2015197 citationsDataRank 8.7
Long‐term variations in the aging of scientific literature: From exponential growth to steady‐state science (1900–2004)
Journal of the American Society for Information Science and Technology2007117 citationsDataRank 0.716

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 35% comes from its base citations and 65% from the citation network (14 citing papers contributed measurable signal).

Base score B(p): log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
Network N(p): Σ over citers of log1p(C_q) ÷ max(outdegree_q, 1). Being cited by a highly-cited paper with few references counts most.
Damping factor d = 0.85: DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
Self-citations excluded: Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.

Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.

Read the full methodology →

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Node colors:CenterData PaperData + Open AccessNon-dataSelected & links| Node size = percentile rank

Authors (1)

Michael ThelwallORCID