Publication: Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data
Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data
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Xu, S., Mariani, M., Lü, L., & Medo, M. (2020). Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data. Journal of Informetrics, 14(1), 101005. https://doi.org/10.1016/j.joi.2019.101005
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Despite the increasing use of citation-based metrics for research evaluation purposes, we do not know yet which metrics best deliver on their promise to gauge the significance of a scientific paper or a patent. We assess 17 network-based metrics by their ability to identify milestone papers and patents in three large citation datasets. We find that traditional information-retrieval evaluation metrics are strongly affected by the interplay between the age distribution of the milestone items and age biases of the evaluated metrics. Outc
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- Xu, Shuqi
- Lü, Linyuan
- Medo, Matúš
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Xu, S., Mariani, M., Lü, L., & Medo, M. (2020). Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data. Journal of Informetrics, 14(1), 101005. https://doi.org/10.1016/j.joi.2019.101005
