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利用LeaderRank识别有影响力的作者
邓启平1,2; 王小梅1
2015-09-25
Source Publication现代图书情报技术
Volume31Issue:9Pages:60-67
Abstract【目的】识别研究领域内有影响力的作者。【方法】将LeaderRank 用于合作网络测度作者影响力, 通过不同的加权算法探讨合作次数和被引频次对重要作者排序的影响, 在此基础上整合两个指标提出CW_LR算法, 从合作和引用两个维度识别有影响力的作者。【结果】CW_LR 算法与被引频次有相关性, 但与被引频次或其他几种加权方法相比, 识别出有影响力的作者与业界公认的更为一致。【局限】只在“信息计量学”领域进行实证, 后续将该方法扩展到其他领域进一步验证其有效性。【结论】同时考虑合作关系强度和引用影响力, 从合作和引用两个维度能更准确地识别出有影响力的作者。
Other 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.
Subtype研究论文
Keyword作者影响力 Leaderrank 合作网
Subject Area科学计量学
Indexed ByGCJC
Project Number71173211
Language中文
Funding Project科学结构特征及其演化动力学分析方法与应用研究
Funding Organization国家自然科学基金项目
Document Type期刊论文
Identifierhttp://ir.las.ac.cn/handle/12502/7928
Collection中国科学院文献情报中心(北京)_情报研究部
Corresponding Author王小梅
Affiliation1.中国科学院文献情报中心
2.中国科学院大学
First Author Affilication中国科学院文献情报中心
Corresponding Author Affilication中国科学院文献情报中心
Recommended Citation
GB/T 7714
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.
APA 邓启平,&王小梅.(2015).利用LeaderRank识别有影响力的作者.现代图书情报技术,31(9),60-67.
MLA 邓启平,et al."利用LeaderRank识别有影响力的作者".现代图书情报技术 31.9(2015):60-67.
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