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Diversity of temporal influence in popularity prediction of scientific publications

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Abstract

Predicting the future influential papers is a challenging issue witch has attracted many attentions. In this paper, we focused on the temporal information of citations to study the popularity prediction problem from the perspective of citation dynamics. The experimental study of the APS citation data shows that the temporal decay rate of the influence of citations is decay with paper’s age, and the decay rate is a power-law distribution. We introduced the diversity of temporal decay rate of the influence of citations to predict the future popularity of papers, and proposed a diverse temporal decay method. The result shows that this method can improve the prediction accuracy compared with other popularity-based prediction methods. More importantly, this method can detect some of the newly published papers that haven’t accumulated many citations but will quickly become popular in the future.

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Notes

  1. http://journals.aps.org/datasets.

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Acknowledgements

This work was supported in part by the National Nature Science Foundation of China under Grants 61603340, 61402413 and Grant 61340058, and in part by the National Nature Science Foundation of Zhejiang Province under Grants LY14F020019 and LZ14F020001.

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Authors and Affiliations

  1. College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, People’s Republic of China

    Yanbo Zhou, Hongbing Cheng, Qu Li & Weihong Wang

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  1. Yanbo Zhou
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  2. Hongbing Cheng
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  3. Qu Li
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  4. Weihong Wang
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Correspondence to Weihong Wang.

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Zhou, Y., Cheng, H., Li, Q. et al. Diversity of temporal influence in popularity prediction of scientific publications. Scientometrics 123, 383–392 (2020). https://doi.org/10.1007/s11192-020-03354-3

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