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Quantifying social asymmetric structures

机译:量化社会不对称结构

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Many social phenomena involve a set of dyadic relations among agents whose actions may be dependent. Although individualistic approaches have frequently been applied to analyze social processes, these are not generally concerned with dyadic relations, nor do they deal with dependency. This article describes a mathematical procedure for analyzing dyadic interactions in a social system. The proposed method consists mainly of decomposing asymmetric data into their symmetric and skew-symmetric parts. A quantification of skew symmetry for a social system can be obtained by dividing the norm of the skew-symmetric matrix by the norm of the asymmetric matrix. This calculation makes available to researchers a quantity related to the amount of dyadic reciprocity. With regard to agents, the procedure enables researchers to identify those whose behavior is asymmetric with respect to all agents. It is also possible to derive symmetric measurements among agents and to use multivariate statistical techniques.
机译:许多社会现象在行动者可能依赖的行动者之间建立了一系列的二元关系。尽管个人主义方法经常被用于分析社会过程,但它们通常不涉及二元关系,也不涉及依存关系。本文介绍了一种用于分析社会系统中二元互动的数学过程。所提出的方法主要包括将非对称数据分解为对称和倾斜对称部分。通过将倾斜对称矩阵的范数除以非对称矩阵的范数,可以获得社会系统的倾斜对称的量化。该计算为研究人员提供了与二元对等互相关的数量。关于代理,该程序使研究人员能够识别行为相对于所有代理不对称的对象。还可以得出代理之间的对称度量,并使用多元统计技术。

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