  Predicting the popularity of scientific publications has attracted many
attentions 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 which paper will receive more citations in the near
future and will be popular. The AD model is a mimic of the attention diffusion
process along the citation networks. The experimental study shows that the AD
model can achieve better prediction accuracy than other networkbased 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 is really critical, because identifying the future highly
cited papers from massive numbers of new papers published each month would
provide very valuable references for researchers.
