A time-dimension paper influence evaluation research:Improvement based on ammaa algorithm
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G350;G644.4

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    Abstract:

    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.

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许恩平,贾娜,李敏,余以胜.一种时间维度的论文影响力评价研究——基于ammaa算法的改进[J].重庆大学学报社会科学版,2021,27(6):111~124

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  • Received:
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  • Online: December 20,2021
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