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.

Individual Differences and Arousal: Implications for the Study of Mood and Memory

Cognition & Emotion(1990)10.1080/02699939008410797Source: DataRank Database

Individual Differences and Arousal: Implications for the Study of Mood and Memory is a research paper published in Cognition & Emotion (1990). On theSindex it has a DataRank of 4.8. It has been cited 95 times, with 94 citing works in its 1-hop citation network.

N/A

4.8DataRank · unranked

4.8

95 citations · base score 4.6

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 14%Citation Network 86%

Base Score Contribution

0.685

From this paper's citation signal

Citation Network Contribution

4.1

From 75 citing papers with measurable signal

Learn more about DataRank methodology →

Top 2 citers driving the network score

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

The relation of strength of stimulus to rapidity of habit‐formation
Journal of Comparative Neurology and Psychology19086,728 citationsDataRank 1.3
Mood and the DRM paradigm: An investigation of the effects of valence and arousal on false memory
Quarterly Journal of Experimental Psychology201335 citationsDataRank 1.4

Why this DataRank?

DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 14% comes from its base citations and 86% from the citation network (75 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 →

Click a node to highlight its connections. Use scroll to zoom. Drag to pan.

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