Chapter 3 - Social network analysis: Measuring, mapping, and modeling collections of connections

Abstract

Social network analysis uses mathematical tools to systematically understand networks, which are made up of vertices (e.g., people) that are connected to one another via edges (e.g., friendship ties). Network metrics help identify who is most important or central in a network, subgroups (i.e., network clusters) of tightly connected people, and the overall network structure (e.g., the density of a network). Social scientists have developed social network analysis and visualization techniques for decades. Network data is represented as an edge list or matrix. Directed edges have a clear origin and destination, while undirected edges do not. Weighted networks include a value associated with the edge. The scope of a network determines if it is an ego network, partial network, or full network. Multimodal networks include vertices of different types, while multiplex networks include edges of different types. Affiliation networks connect people based on shared affiliations (e.g., club).