Abstract
[Purpose/meaning] Solving the problem that h-index and h-type index lack of comprehensive evaluation of scientists’ overall academic contribution. [Method/process] Considering the contribution of scientists’ first h academic papers, this paper proposed two weighted h-index model which are named hw-index and hw_t-index, and then used the data from 30 active Chinese scholars in Library and Information Science field for empirical analysis. [Results/conclusion] Revealing highly cited papers and considering the contribution of scientists’ every paper, hw-index not only weakens the influence of self-citation on the results, but also makes it easy to distinguish scientists’ contributions. The hw_t-index focuses on the scientists’ papers in recent years, and it also considers their past contributions. Therefore, in short term evaluation, the hw_t-index is more reasonable for young scientists who have made a great contribution in the past years. Potential scholars can be identified by the way of comparing hw-index and hw_t-index.
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Publication of this article was funded by National Social Science Foundation of China (Grant numbers 16BTQ071).
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Feng, GH., Mo, XQ. (2019). Research on the Evaluation of Scientists Based on Weighted h-index. In: Bucciarelli, E., Chen, SH., Corchado, J. (eds) Decision Economics. Designs, Models, and Techniques for Boundedly Rational Decisions. DCAI 2018. Advances in Intelligent Systems and Computing, vol 805. Springer, Cham. https://doi.org/10.1007/978-3-319-99698-1_14
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DOI: https://doi.org/10.1007/978-3-319-99698-1_14
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