[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.
邓启平, 王小梅. 利用LeaderRank识别有影响力的作者[J]. 现代图书情报技术, 2015, 31(9): 60-67.
Deng Qiping, Wang Xiaomei. Identifying Influential Authors Based on LeaderRank. New Technology of Library and Information Service, 2015, 31(9): 60-67.
[1] Ding Y, Yan E, Frazho A, et al. PageRank for Ranking Authors in Co-citation Networks [J]. Journal of the American Society for Information Science and Technology, 2009, 60(11): 2229-2243.
[2] Fiala D, Rousselot F, Je?ek K. PageRank for Bibliographic Networks [J]. Scientometrics, 2008, 76(1): 135-158.
[3] Burt R S. The Network Structure of Social Capital [J]. Research in Organizational Behavior, 2000, 22: 345-423.
[4] Mutschke P. Mining Networks and Central Entities in Digital Libraries. A Graph Theoretic Approach Applied to Co-author Networks [C]. In: Proceedings the 5th International Symposium on Intelligent Data Analysis, Berlin, Germany. 2003: 155-166.
[5] Yin L, Kretschmer H, Hanneman R A, et al. Connection and Stratification in Research Collaboration: An Analysis of the COLLNET Network [J]. Information Processing & Management, 2006, 42(6):1599-1613.
[6] 徐玲, 胡海波, 汪小帆. 一个中国科学家合作网的实证分析[J]. 复杂系统与复杂性科学, 2009, 6(1): 20-28. (Xu Ling, Hu Haibo, Wang Xiaofan. Empirical Analysis of a China Scientists Collaboration Network [J]. Complex Systems and Complexity Science, 2009, 6(1): 20-28.)
[7] Yan E, Ding Y. Applying Centrality Measures to Impact Analysis: A Coauthorship Network Analysis [J]. Journal of the American Society for Information Science and Technology, 2009, 60(10): 2107-2118.
[8] Liu X, Bollen J, Nelson M L, et al. Co-authorship Networks in the Digital Library Research Community [J]. Information Processing & Management, 2005, 41(6): 1462-1480.
[9] 丁洁兰.科研人员学术影响力二维测度研究[D]. 北京: 中国科学院研究生院, 2011.(Ding Jielan. Two-Dimensional Research on Measuring the Academic Impact of Researchers [D]. Beijing: The Graduate School of Chinese Academy of Sciences, 2011.)
[10] 杜建, 张玢, 唐小利.作者学术影响力双重测度探讨: 引用影响力和合作影响力之整合[J]. 情报学报, 2014, 33(4): 388-395. (Du Jian, Zhang Bin, Tang Xiaoli. Two-dimensional Measurement for Academic Influence of Researchers: Integration of Citation Impact and Collaboration Impact [J]. Journal of the China Society for Scientific and Technical Information, 2014, 33(4): 388-395.)
[11] Börner K, Dall'Asta L, Ke W, et al. Studying the Emerging Global Brain: Analyzing and Visualizing the Impact of Co-authorship Teams [J]. Complexity, 2005, 10(4): 57-67.
[12] Yan E, Ding Y. Discovering Author Impact: A PageRank Perspective [J]. Information Processing & Management, 2011, 47(1): 125-134.
[13] Lü L, Zhang Y, Yeung C H, et al. Leaders in Social Networks, the Delicious Case[J]. Plos One, 2011, 6(6): e21202.
[14] Li Q, Zhou T, Lü L Y, et al. Identifying Influential Spreaders by Weighted LeaderRank [J]. Physica A: Statistical Mechanics and Its Applications, 2014, 404: 47-55.
