Quantifying spatial–temporal citation diffusion of individual papers in knowledge space

Shuang Zhang, Feifan Liu and Haoxiang Xia

Journal of the Association for Information Science & Technology, 2025, vol. 76, issue 12, 1682-1700

Abstract: Despite extensive efforts to reveal temporal patterns of citation dynamics for individual papers, the spatial–temporal patterns, which reflect a coupled process involving the accumulation of citations over time and their concentration or dispersion in the high‐dimensional knowledge space, remain largely unexplored. Drawing on millions of papers in seven large‐scale disciplines, we apply document representation algorithms capturing semantic associations to construct citation diffusion trajectories in the embedded disciplinary knowledge landscape. We find a tendency toward semantically localized citation mobility patterns, characterized by Gaussian‐distributed citation scopes and exponentially distributed citation distances. Further analysis investigates the role of early citation diffusion characteristics in shaping citation accumulation, revealing a positive correlation between initial citation diffusion breadth and citation growth, which significantly amplifies long‐term impact among papers with comparable early citation counts. We identify distinct spatial–temporal citation diffusion patterns for novel and disruptive papers. While highly cited papers attract significant attention both in the early stages and over time, their citation diffusion typically follows conventional patterns, with most citations spanning shorter knowledge distances. Novel papers and disruptive papers, despite garnering fewer and delayed citations, tend to attract longer‐distance citations early on and generate more extensive and distant impacts within the knowledge space.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jinfst:v:76:y:2025:i:12:p:1682-1700

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