Predicting the popularity of scientific publications by an age-based diffusion model

Yanbo Zhou, Qu Li, Xuhua Yang and Hongbing Cheng

Journal of Informetrics, 2021, vol. 15, issue 4

Abstract: Predicting the popularity of scientific publications has attracted much attention from various disciplines. In this paper, we focus on the popularity prediction problem of scientific papers, and propose an age-based diffusion (AD) model to identify papers that will receive more citations and be popular in the near future. The AD model mimics the attention diffusion process along the citation networks. An experimental study shows that the AD model can achieve better prediction accuracy than other benchmark methods. For some newly published papers that have not accumulated many citations but will be popular in the near future, the AD model can substantially improve their rankings. This improvement is critical, because identifying future highly cited papers from large numbers of new papers published each month would provide very valuable references for researchers.

Keywords: Popularity prediction; Citation network; Diffusion process (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:15:y:2021:i:4:s1751157721000481

DOI: 10.1016/j.joi.2021.101177

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