Blockmodeling for analysis of social structures: theoretical and methodological foundations

T. Shcheglova, D. Maltseva, Aryuna Kim
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引用次数: 1

Abstract

The article discusses the features of blockmodeling as a class of methods for clustering network data in the analysis of social structures. Blockmodeling is considered as an approach to the analysis of social structure, which combines network components into groups (clusters) based on their equivalent structural positions. The basic concepts of blockmodeling are described – matrix, matrix image, cluster, clustering, position, block, blockmodel; an illustrating example is given. The concept of equivalence is presented, and two types of equivalence, structural and regular, are described. The main approaches of blockmodeling – indirect and direct – and related methods and algorithms are presented. For each approach, examples of the practical application in social sciences are provided. Other methods of blockmodeling (stochastic blockmodeling) and similar methods of subgroups detection in networks are mentioned. It is shown that the methodology of blockmodeling has heuristic potential for analyzing social structures and is promising for identifying cohesive groups and determining the role and structural positions of individuals within them. In conclusion, the open questions and limitations of this research methodology are discussed.
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社会结构分析的块建模:理论和方法基础
本文讨论了块建模作为社会结构分析中聚类网络数据的一类方法的特点。块建模被认为是一种分析社会结构的方法,它将网络组件根据它们的等效结构位置组合成组(簇)。描述了块建模的基本概念——矩阵、矩阵图像、聚类、聚类、位置、块、块模型;给出了一个举例说明。提出了等价的概念,并描述了结构等价和规则等价的两种类型。介绍了块建模的主要方法——间接建模和直接建模,以及相关的方法和算法。对于每种方法,都提供了在社会科学中的实际应用示例。文中还提到了网络中其他的块建模方法(随机块建模)和类似的子群检测方法。研究表明,块建模方法在分析社会结构方面具有启发式潜力,并且有望识别有凝聚力的群体,并确定个体在其中的角色和结构位置。最后,讨论了该研究方法的开放性问题和局限性。
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