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Ranking scientific publications considering the aging characteristics of citations

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Abstract

Ranking the significance of scientific publications has been a challenging topic for a long time. So far, many ranking methods have been proposed, one of which is the well-known PageRank algorithm. In this paper, we introduce aging characteristics to the PageRank algorithm via considering only the first 10 year citations when aggregating resource from different nodes. The validation of our new method is performed on the data of American Physical Society journals. The results indicate that taking into account aging characteristics improves the performance of the PageRank algorithm in terms of ranking accuracy for both papers and authors. Though our method is only applied to citation networks in this paper, it can be naturally used in many other real systems and similar improvements are expected.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant Nos. 61603046, 61374175, 61573065) and the Natural Science Foundation of Beijing (Grant No. L160008).

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Authors and Affiliations

  1. School of Systems Science, Beijing Normal University, Beijing, 100875, People’s Republic of China

    Yanan Wang, An Zeng, Ying Fan & Zengru Di

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  1. Yanan Wang
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  2. An Zeng
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  3. Ying Fan
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  4. Zengru Di
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Correspondence to An Zeng or Ying Fan.

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Wang, Y., Zeng, A., Fan, Y. et al. Ranking scientific publications considering the aging characteristics of citations. Scientometrics 120, 155–166 (2019). https://doi.org/10.1007/s11192-019-03117-9

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