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Community Detection in Learning Networks Using R

  • Ángel Hernández-García,
  • Carlos Cuenca-Enrique,
  • Adrienne Traxler,
  • Sonsoles López-Pernas,
  • Miguel Ángel Conde-González,
  • Mohammed Saqr

摘要

In 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.