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作 者:闫晓慧 杨杰 杨文霞[2,3] 王昊 邓三鸿[2,3] Yan Xiaohui;YangAlex Jie;Yang Wenxia;Wang Hao;Deng Sanhong(Investigation Department,Shanxi Police College,Taiyuan 030401;School of Information Management,Nanjing University,Nanjing 210023;Key Laboratory of Data Engineering and Knowledge Services in Provincial Universities(Nanjing University),Nanjing 210023)
机构地区:[1]山西警察学院侦查系,太原030401 [2]南京大学信息管理学院,南京210023 [3]数据工程与知识服务省高校重点实验室(南京大学),南京210023
出 处:《图书情报工作》2025年第2期96-107,共12页Library and Information Service
基 金:国家社会科学基金项目“大数据环境下学术成果真实价值与影响的实时预测及长期评价研究”(项目编号:19BTQ062)研究成果之一。
摘 要:[目的/意义]传统计量指标在学者影响力评价时未考虑学术合作网络内外部的差异,本文提出合作网络外部被引量和外部h指数等学者合作网络外部影响力评价指标,为学者真实学术影响力评价提供依据。[方法/过程]以美国物理学会数据集的463348篇研究论文及其234086位消歧学者的数据作为样本,从全局合作网络抽取学者的自我中心合作网络,基于学者合作网络对内部与外部进行区分,提出外部被引量和外部h指数等学者合作网络外部影响力评价指标,结合基准计量指标进行一致性检验,基于诺贝尔奖、沃尔夫奖和狄拉克奖等物理学奖项数据证明合作网络外部影响力评价指标的有效性和优越性。[结果/结论]研究发现,学者合作网络内部与外部影响力分布存在显著差异,本文提出的学者合作网络外部影响力与基准指标一致性较强,收敛有效性分析表明外部被引量和外部h指数相比于基准指标能够更准确地识别获奖学者,表明合作网络外部影响力反映了学者的真实影响力,在学术成就中扮演着关键作用,本文提出的新指标对于构建未来人才评价体系和破“五唯”有着启示作用。[Purpose/Significance]Traditional bibliometric indicators fail to capture the distinctions between the internal and external dimensions of academic collaboration networks.This paper introduces new metrics,such as external citations and the external h-index,for evaluating the external impact of scholarly collaboration networks,providing a foundation for a more authentic assessment of scholars'academic influence.[Method/Process]Utilizing data from the American Physical Society,which includes 463,348 research papers and 234,086 disambiguated authors,this study extracts scholars'ego-centric collaboration networks from the global network.It distinguishes between internal and external influences within these networks and introduces metrics such as the external citation count and the external h-index.These are tested for consistency against traditional bibliometric indicators and validated using data from prestigious physics awards such as the Nobel Prize,the Wolf Prize,and the Dirac Prize,to demonstrate the effectiveness and superiority of the external impact metrics.[Result/Conclusion]The study reveals significant disparities in the distribution of internal versus external influence within scholarly collaboration networks.The proposed external impact metrics introduced are highly consistent with traditional indicators.Convergence validity analysis shows that the external citation count and external h-index are more precise in identifying award-winning scholars compared to traditional metrics.These findings suggest that the external influence of collaboration networks reflects the true impact of scholars and plays a crucial role in academic achievements.The new metrics proposed here offer insightful implications for constructing future talent evaluation systems and breaking away from the“five only”criteria,providing a pathway for reform in academic assessments.
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