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A time dimension of paper influence evaluation research:Improvement based on AMMAA algorithm
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作者 Na Jia Yisheng Yu 《Data Science and Informetrics》 2022年第1期81-96,共16页
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 ... 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.We used Web of Science as the data source and focused on the paper published by the authors of Chinese library and info rmation science,to calculate the ammaa value and t-ammaa value of these papers,and then obtained the ammaa value and t-ammaa value of the scholar.The result ranking of the two algorithms and the scholar’s H-value ranking are normalized for empirical comparison and analysis.The results show that t-ammaa algorithm considering the cited times,the cited threshold limit,the co-authors’number,and the temporal heterogeneity of the cited papers,is a more reasonable measurement method for evaluating the influence of scholars.It can not only comprehensively evaluate the influence of single author and co-authored paper,but also eliminate the influence brought by time factor. 展开更多
关键词 AMMAA algorithm Temporal heterogeneity Multi-author paper influence Author influence Evaluation index Altmetrics
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