Author:
Hernández-García Ángel,Cuenca-Enrique Carlos,Traxler Adrienne,López-Pernas Sonsoles,Conde-González Miguel Ángel,Saqr Mohammed
Abstract
AbstractIn the field of social network analysis, understanding interactions and group structures takes a center stage. This chapter focuses on finding such groups, constellations or ensembles of actors who can be grouped together, a process often referred to as community detection, particularly in the context of educational research. Community detection aims to uncover tightly knit subgroups of nodes who share strong connectivity within a network or have connectivity patterns that demarcates them from the others. This chapter explores various algorithms and techniques to detect these groups or cohesive clusters. Using well-known R packages, the chapter presents the core approach of identifying and visualizing densely connected subgroups in learning networks.
Publisher
Springer Nature Switzerland