Prediction of citation dynamics of individual papers

@article{Golosovsky2019PredictionOC,
  title={Prediction of citation dynamics of individual papers},
  author={Michael Golosovsky},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.00867}
}
We apply stochastic model of citation dynamics of individual papers developed in Chap. 3 to forecast citation career of individual papers. We focus not only on the estimate of the future citations of a paper but on the probabilistic margins of such estimate as well. 
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References

SHOWING 1-10 OF 37 REFERENCES
Citation statistics from 110 years of physical review
Publicly available data reveal long-term systematic features about citation statistics and how papers are referenced. The data also tell fascinating citation histories of individual articles.
Predicting the long-term citation impact of recent publications
A data analytic approach to quantifying scientific impact
Discontinuities in citation relations among journals: self-organized criticality as a model of scientific revolutions and change
Using 3-year moving averages of the complete Journal Citation Reports 1994–2016 of the Science Citation Index and the Social Sciences Citation Index (combined), we analyze links between citing and…
Citation count prediction: learning to estimate future citations for literature
TLDR
This paper has implemented a system which takes a series of features of a particular publication as input and produces as output the estimated citation counts of that article after a given time period and considers several regression models to formulate the learning process and evaluate their performance based on the coefficient of determination (R-square).
The first-mover advantage in scientific publication
TLDR
It is suggested that some later-published papers, albeit only a small fraction, that buck the trend and attract significantly more citations than theory predicts are probably worthy of the authors' attention.
Early identification of important patents: Design and validation of citation network metrics
Quantifying Long-Term Scientific Impact
TLDR
A mechanistic model is derived for the citation dynamics of individual papers, allowing us to collapse the citation histories of papers from different journals and disciplines into a single curve, indicating that all papers tend to follow the same universal temporal pattern.
Early citation counts correlate with accumulated impact
TLDR
There is a statistically highly significant correlation between initial (years 1-2) and later (years 3-10) citations in six research categories across the life and physical sciences and it seems reasonable to conclude that leading indicators of research excellence could be developed.
Better late than never? On the chance to become highly cited only beyond the standard bibliometric time horizon
TLDR
This study is focussed on a large-scale analysis of the citation history of all papers indexed in the 1980 annual volume of the Science Citation Index to analyse whether the share of delayed recognition papers is significant and whether such papers are typical of the work of their authors at that time.
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