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| Identifying Influential Authors Based on LeaderRank |
| Deng Qiping1,2, Wang Xiaomei1 |
1 National Science Library, Chinese Academy of Sciences, Beijing 100190, China;
2 University of Chinese Academy of Sciences, Beijing 100049, China |
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Abstract [Objective] Provide an alternative perspective for identifying influential authors. [Methods] This paper uses the weighted LeaderRank algorithm to measure author's impacts in coauthorship network. Respectively validates the effects of citations and the number of cooperation on sorting influential authors through different weighted algorithms. And base on the validation a new weighted algorithm named CW_LR is proposed by integrating these two factors. [Results] CW_LR algorithm is interrelated with citations, but compared with citations or other weighted algorithms, the result of CW_LR algorithm is more consistent with expert knowledge. [Limitations] This algorithm is tested in the informetrics research community, while further effectiveness validation in other research community is required. [Conclusions] The strength of cooperation and citation impact are considered at the same time in CW_LR algorithm, and this algorithm identifies the influential author more accurately from two dimensions.
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Received: 02 February 2015
Published: 06 April 2016
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