In the fall of 2012, I got to design & lead the weekly labs for a network seminar at USC. I also worked on the methods portion of the syllabus for the class. COMM 645: Communication Networks is a PhD-level course taught by Peter Monge. The labs cover a range of network tools – from the classic UCINET program through NodeXL and Gephi, to R introduction, Statnet, exponential random graph and actor-based modeling. Since the handouts & script examples may be useful for people outside the course, I’m sharing them here.

[*Update 2014*] The materials listed below, along with sample datasets and lab assignments, are now available as a GitHub Repository here.

- Basics of network formats handout (PDF download).
- Intro to UCINET and NetDraw handout (PDF download).
- Intro to NodeXL handout (PDF download).
- Intro to Gephi handout (PDF download).
- Intro to R (script example).
- Networks in R using Statnet/SNA/Network (script example).
- Network correlation & regression in R. QAP & MRQAP.

Conditional uniform graph (CUG) tests (script example). - Exponential random graph modeling basics handout (PDF download).

Exponential random graph modeling in R (script example). - Actor-based modeling basics handout (PDF download).

Actor-based modeling in R (script example).