Social networks shape everything, from how information spreads online and how teams collaborate, to how influence, innovation, and trust emerge in organisations and society. This short course introduces Social Network Analysis (SNA) as a powerful framework for understanding complex social, organisational, and technological systems. Designed for a diverse audience, the course blends foundational theory with hands-on methods, making it suitable for students, academics, data analysts, policymakers, and industry practitioners who want to turn relational data into actionable insights.

What You’ll Learn

• Core theories of social networks, including structure, ties, centrality, cohesion, and diffusion
• How to model and analyse network data using established SNA methods
• Practical techniques to visualise and interpret networks
• Applications of SNA in areas such as social media, organisations, marketing, innovation, epidemiology, and policy
• How network thinking can inform strategic decision-making in real-world settings.

How the Course Works

The course combines conceptual lectures, real-world examples, and hands-on exercises. Participants will learn not just what networks are, but how to analyse them and why they matter across disciplines and industries. No prior background in network analysis is required. Basic familiarity with data or analytical thinking is helpful, but the course is structured to be accessible to newcomers while still offering depth for more experienced participants.

About Your Tutor

Dr. Narisong Huhe is a Senior Lecturer (Associate Professor) at the University of Strathclyde. His research interests centre on the application of network analysis to the study of political and social phenomena. His work has been published in journals including the British Journal of Political Science, Social Networks, Political Research Quarterly, Journal of European Public Policy, and Political Studies.

Discounted fee of £450 available to University staff/students, government and not-for-profit organisations only. Enter discount code MC2H-F297GD73YUI8 at checkout.
Fee is £750 for all other participants.