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A New Centrality Measure for Social Network Analysis Applicable to Bibliometric and Webometric Data

机译:适用于文献计量学和网络计量学数据的社交网络分析的新中心度度量

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摘要

In the literature there are a large number of publications in sociology, in computer science or in information sciences, as well as in studies of collaboration in science describing the studies of social networks with unweighted ties because measures involving unweighted ties are easier to calculate. It is not surprising that there are few studies on networks with weighted ties since they not only need more complex formulas but need a process of quantification when quantitative empirical data are not directly available. However quantitative empirical data are directly available under the condition of using bibliometric or webometric data.In conclusion new complex measures of the degree centrality are introduced including weighted ties possible for use of the analysis of co-authorship or citation networks. Both co-authorship relations and citations are well quantified data (weighted ties).These new measures are applied to a co-authorship network as an example
机译:在文献中,社会学,计算机科学或信息科学以及科学合作研究中都有大量出版物描述了不加权关系的社交网络的研究,因为涉及不加权关系的度量更易于计算。不足为奇的是,很少有关于加权关系网络的研究,因为它们不仅需要更复杂的公式,而且在无法直接获得定量经验数据时也需要进行量化过程。但是,在使用文献计量学或网络计量学数据的条件下,可以直接获得定量的经验数据。总之,引入了新的程度中心度复杂度量,包括可能用于共同作者或引文网络分析的加权关系。共同作者关系和引文都是量化良好的数据(加权关系),这些新方法以共同作者网络为例

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  • 年度 2006
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