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Regarding weight assignment algorithms of main path analysis and the conversion of arc weights to node weights
Scientometrics ( IF 3.5 ) Pub Date : 2020-04-24 , DOI: 10.1007/s11192-020-03468-8
Chung-Huei Kuan

In a recent article, Liu et al. (Scientometrics 119(1):379–391, 2019) elaborated a number of issues of the main path analysis (MPA) and provided valuable insight into its application. Among these issues, the authors compared three weight assignment algorithms and suggested that one is preferable in simulating the knowledge diffusion scenario. The authors further stated that one may convert a document’s related arc weights assigned by these algorithms into a weight of the document itself by taking the average of its incident and outgoing arc weights, and claimed that a document highly weighted as such may be considered as having a great impact. In this Letter, we address these two issues: (1) choice of weight assignment algorithms, and (2) conversion of arc weights to node weights from a different perspective and provide alternative suggestions, in the hope that we may enrich the discussion for MPA.

中文翻译:

关于主路径分析的权重分配算法以及弧权重到节点权重的转换

在最近的一篇文章中,刘等人。(Scientometrics 119(1):379–391, 2019) 阐述了主路径分析 (MPA) 的许多问题,并为其应用提供了宝贵的见解。在这些问题中,作者比较了三种权重分配算法,并建议一种更适合模拟知识扩散场景。作者进一步表示,可以通过取其事件和输出弧权重的平均值,将这些算法分配的文档相关的弧权重转换为文档本身的权重,并声称如此高权重的文档可能被认为具有很大的影响。在这封信中,我们解决了这两个问题:(1)权重分配算法的选择,以及(2)从不同的角度将弧权重转换为节点权重并提供替代建议,
更新日期:2020-04-24
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