Advanced Method in Social Network Analysis

In previous chapters, we discuss the social network analysis basics such as nodal degree centrality, measures of dyadic pairs, cliques and subgroups, as well as centralization and density measures at the whole network level. This chapter addresses more advanced topics such as mapping and clustering, bipartite network, and ERGM. It starts with the mapping technique such as MDS and hierarchical clustering to depict the structuration and configuration of social networks. Then it introduces bipartite network that involves heterogenous sets of nodes in social network analysis. It concludes with a discussion of Exponential Random Graph Modeling (ERGM), an unique model method that tries to explain the social network outcomes.