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TimeRank: A dynamic approach to rate scholars using citations

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  • Franceschet, Massimo
  • Colavizza, Giovanni

Abstract

Rating has become a common practice of modern science. No rating system can be considered as final, but instead several approaches can be taken, which magnify different aspects of the fabric of science. We introduce an approach for rating scholars which uses citations in a dynamic fashion, allocating ratings by considering the relative position of two authors at the time of the citation among them. Our main goal is to introduce the notion of citation timing as a complement to the usual suspects of popularity and prestige. We aim to produce a rating able to account for a variety of interesting phenomena, such as positioning raising stars on a more even footing with established researchers. We apply our method on the bibliometrics community using data from the Web of Science from 2000 to 2016, showing how the dynamic method is more effective than alternatives in this respect.

Suggested Citation

  • Franceschet, Massimo & Colavizza, Giovanni, 2017. "TimeRank: A dynamic approach to rate scholars using citations," Journal of Informetrics, Elsevier, vol. 11(4), pages 1128-1141.
    • Handle: RePEc:eee:infome:v:11:y:2017:i:4:p:1128-1141
    DOI: 10.1016/j.joi.2017.09.003
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    File URL: http://www.sciencedirect.com/science/article/pii/S1751157717301025
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    Cited by:

    1. Zeng, Tong & Wu, Longfeng & Bratt, Sarah & Acuna, Daniel E., 2020. "Assigning credit to scientific datasets using article citation networks," Journal of Informetrics, Elsevier, vol. 14(2).

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