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| Evaluation of Authors Influence Based on Principal Component Analysis and a Neural Network |
| Li Qinmin, and Guo |
| Business School, University of Shanghai for Science and Technology, Shanghai 200093 |
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Abstract To better analyze the influence of scientific researchers, a comprehensive evaluation of influence is performed by combining six factors of researchers’ influence with the method of multivariate statistics. First, the initial H index is obtained and improved. A comprehensive index based on WRSR (weighted rank sum ratio) and the principal component from principal component analysis is then established. Finally, a prediction model is obtained by training a neural network. The empirical results show that, compared with other traditional indicators, the method has good distinction, correlation, and comprehensiveness, enabling the precise evaluation of the influence of scientific researchers.
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Received: 05 June 2018
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