Abstract
Nowadays scientific evaluation is becoming increasingly important and necessary in many cases, such as faculty hiring, funding and promotion. Among existing evaluation metrics for individual performance, h-index is the most famous indicator and achieves a prominent role since its publication. However, h-index is inapplicable to comparing individuals from different scientific disciplines, primarily because it cannot handle the huge difference in collaboration habits and citation practices across disciplines. Such a shortcoming of h-index is rooted in its arbitrary definition, comparing two quantities with quite different scales, i.e., citation count for scientific impact and publication count for productivity. To combat this problem, we propose a new evaluation measure, \(h_u\)-index, which unifies citation count and publication count into the same scale. We theoretically analyze the relationship between \(h_u\)-index, h-index and other variants of h-index. We also study the behavior of \(h_u\)-index in empirical cases and researcher ranking tasks. Experimental results demonstrate that \(h_u\)-index has superior performance than h-index and achieves a better comparison of individuals across disciplines.
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PACS 2010 alphabetical index. https://publishing.aip.org/wp-content/uploads/2019/01/PACS_2010_Alpha.pdf.
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Acknowledgements
This work is funded by the National Key R&D Program of China under Grant No. 2018YFB1402600 and the National Natural Science Foundation of China under Grant Nos. 91746301 and U1911401. This work is supported by Beijing Academy of Artificial Intelligence (BAAI) under the Grant No. BAAI2019QN0304. Huawei Shen is also funded by K.C. Wong Education Foundation.
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Li, S., Shen, H., Bao, P. et al. \(h_u\)-index: a unified index to quantify individuals across disciplines. Scientometrics 126, 3209–3226 (2021). https://doi.org/10.1007/s11192-021-03879-1
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DOI: https://doi.org/10.1007/s11192-021-03879-1