“Analyzing Social Structure using Multigraph Representations”
Presentation @ Centre Marc Bloch, Berlin
Nov 2, 2022
Abstract
Multivariate networks consist of a vertex set with at least one type of edge between pairs of vertices and with numerical and/or qualitative attributes on the vertices and the edges. These networks provide a more accurate representation of social structure than univariate networks, but analysing them introduce technical and computational complexity. In this presentation, we consider exploratory and confirmatory analysis of multivariate networks represented as multigraphs. Multigraph data structure is described with examples of their natural appearance, together with a description of the possibility to obtain multigraphs using blocking, aggregation and scaling. Two random multigraph models are presented and several statistics under these models are derived. It is shown how these statistics can be used to analyse local and global network properties in order to convey important social phenomena and processes. Applications are used to illustrate the applicability of the presented approach, including when analysing the gendered inequalities in popular cinema by using dialogue networks. Moreover, some examples are provided on how to use the package ‘multigraphr’ in the statistical software R to perform the analysis.