摘要
针对目前h指数存在的不足,学界尚缺乏一种综合有效的评价指标,为此,笔者期待介绍一种论文评价的ammaa算法,并提出一种融入时间维度的优化算法,即t;mmaa算法,通过对论文影响力的评价来反映学者个人的影响力评价。研究过程中,以Web of Science作为数据源,聚焦国内图情领域作者发文,计算论文ammaa值及t;mmaa值,进而得出学者的ammaa值及t;mmaa值,并将两种算法结果排名与学者H值排名通过归一化处理,进行实证对比分析。结果表明:t;mmaa算法综合考虑发文被引次数、被引次数的阙值限制、合著者人数及论文被引时间的异质性,既可以对独著和合著论文影响力进行综合性评价,也可以消除时间因素带来的影响,是一种更为合理的学者和论文影响力评价计量方法。
Aiming at the deficiency of h index and the lack of a comprehensive and effective evaluation index, this paper introduces an ammaa algorithm for paper evaluation, and proposes an optimization algorithm integrating time dimension: t-ammaa algorithm, which reflects the influence evaluation of individual scholars through the evaluation of paper influence. Using Web of Science as the data source and focusing on the papers published by domestic authors in the field of library and information science, the ammaa value and t-ammaa value of these papers are calculated, and then the ammaa value and t-ammaa value of the scholars are obtained. The result ranking of the two algorithms and the scholars’ H-value ranking are normalized for empirical comparison and analysis. The results show that t-ammaa algorithm considers the cited times, the cited threshold limit, co-author number and the temporal heterogeneity of the cited papers. It can not only comprehensively evaluate the influence of single-author and co-authored paper, but also eliminate the influence brought by time factor. It is a more reasonable measurement method for evaluating the influence of scholars and papers.
作者
许恩平
贾娜
李敏
余以胜
XU Enping;JIA Na;LI Min;YU Yisheng(Science and Technology Department,South China Normal University,Guangzhou 510000,P.R.China;School of Economics and Management,South China Normal University,Guangzhou 510000,P.R.China)
出处
《重庆大学学报（社会科学版）》
CSSCI
北大核心
2021年第6期111-124,共14页
Journal of Chongqing University(Social Science Edition)
基金
国家社会科学基金项目“基于用户行为动机的Altmetrics评价模型构建与实证研究”(18BTQ075)。
