The course is designed for an interdisciplinary cohort of participants, from a wide range of methodological backgrounds in quantitative and qualitative research.
We will cover three essentials: (1) problem framing and jargon, (2) data and software, and (3) analytic techniques and interpretation of results. What to expect:
Pre-course:
- Interdisciplinary readings (network science, social network analysis, political network analysis, organizational network analysis, policy network analysis)
- Software fundamentals (tutorials of R and Gephi)
Course:
- Day 1 – Social Network Analysis & Network Data – Applications
- Day 2 – Insights at the Network Level – Understanding Complex Ecosystems
- Day 3 – Insights at the Community Level – Understanding Groups
- Day 4 – Insights at the Individual Level – Understanding Key Actors
- Day 5 – Causality in Networks – Intro to Inferential Network Analysis & Impact Assessment