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This research addresses the need to understand how quickly scientific papers gain citations. Survival analysis is employed to model the time until papers receive their first citation. Leveraging the Kaplan-Meier estimator and the discrete-time model, the study evaluates the likelihood of citation over time and analyses factors influencing citation speed, focusing on the number of coauthors, the journal's impact factor, and the number of cited references. The approach is applied to a set of top journals in the Information Science & Library Science subject category defined by Web of Science. The main findings reveal notable differences in the citation probability between different journals, with specific sources exhibiting faster citation rates. By modelling citation speed, the study offers a data-driven basis for informed journal selection, aimed at maximising early scholarly recognition. It provides a practical, empirically grounded decision-support framework for authors seeking timely scientific appraisal through strategic journal selection. • The study applies survival analysis to model time until first citation in a probabilistic framework to assess citation speed. • A discrete-time survival tool is used to investigate citation patterns across journals. • The number of authors, journal impact factor, and number of cited references are examined for their effect on citation speed. • Results show significant differences in citation probabilities across journals, with sources achieving faster citation rates.
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Stored only when both papers are in the corpus — 8 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.