blockmodeling

M. Matjašič, M. Cugmas, A. Žiberna
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引用次数: 1

摘要

本文提出了R包块建模,它主要是作为有值网络的广义块建模(更广泛的块建模)的实现,其中假设关系的值至少在区间尺度上被测量。块建模是(社会)网络分析中最常用的方法之一,它处理所研究单元(例如,人、组织、期刊等)之间的关系或联系的分析。R包块建模实现了二值网络广义块建模的几种方法。广义块建模通常用于根据网络中节点的链路结构对其进行聚类。本文总结了二元和有值网络的广义块建模的理论基础,并通过将R包块建模应用于经验数据集来说明它的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
blockmodeling
This paper presents the R package blockmodeling which is primarily meant as an implementation of generalized blockmodeling (more broadly blockmodeling) for valued networks where the values of the ties are assumed to be measured on at least interval scale. Blockmodeling is one of the most commonly used approaches in the analysis of (social) networks, which deals with the analysis of relationships or connections, between the units studied (e.g., peoples, organizations, journals etc.). The R package blockmodeling implements several approaches for the generalized blockmodeling of binary and valued networks. Generalized blockmodeling is commonly used to cluster nodes in a network with regard to the structure of their links. The theoretical foundations of generalized blockmodeling for binary and valued networks are summarized in the paper while the use of the R package blockmodeling is illustrated by applying it to an empirical dataset.
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