Learning Outcomes:
On completion of this module students will be able to:
· Critically evaluate theoretical foundations and computational methods of Social Network Analysis across diverse social science applications
· Design and implement network data collection strategies appropriate for research questions in communication, epidemiology, organizational studies, and related fields
· Apply advanced computational techniques using R programming to process, analyze, and visualize both static and dynamic social network data
· Interpret network metrics, structural properties, and positional analyses to explain individual-level attributes and collective social phenomena
· Synthesize relational thinking approaches with traditional social science methodologies to address complex research problems
· Evaluate the methodological strengths and limitations of network analysis approaches in empirical research contexts