Network analysis of 2-mode data
Network analysis of 2-mode data
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DOI：
10.1016/s0378-8733(96)00301-2
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发表时间：
1997-08-01
期刊：
影响因子：
3.1
通讯作者：
Everett, MG
中科院分区：
文献类型：
--
作者：
Borgatti, SP;Everett, MG
网络分析与传统社会科学的区别在于标准数据集的二元性质。在传统社会科学中，我们研究个体的一元属性，而在网络分析中，我们研究个体对的二元属性。这些二元属性（例如，社会关系）可以通过1模方阵以矩阵形式表示。相比之下，传统社会科学中的数据被表示为2模矩阵。然而，网络分析并没有完全脱离传统社会科学，并且经常需要收集和分析2模矩阵，此外，网络分析中开发的一些方法也可用于分析非网络数据。本文提出并讨论了将传统网络分析技术应用于2模数据的方法，以及开发新技术，详细涵盖了三个领域：将2模数据显示为网络、检测聚类和测量中心性。
Network analysis is distinguished from traditional social science by the dyadic nature of the standard data set. Whereas in traditional social science we study monadic attributes of individuals, in network analysis we study dyadic attributes of pairs of individuals. These dyadic attributes (e.g, social relations) may be represented in matrix form by a square 1-mode matrix, In contrast, the data in traditional social science are represented as 2-mode matrices. However, network analysis is not completely divorced from traditional social science, and often has occasion to collect and analyze 2-mode matrices, Furthermore, some of the methods developed in network analysis have uses in analysing non-network data, This paper presents and discusses ways of applying and interpreting traditional network analytic techniques to 2-mode data, as well as developing new techniques, Three areas are covered in detail: displaying 2-mode data as networks, detecting clusters and measuring centrality.