Course Program, SNA School 2013

1. SNA introduction (B.Lind)
2. Automated Discovery of Social Networks from Online Data. Part 1: Data retrieval (A.Gruzd)
3. Automated Discovery of Social Networks from Online Data. Part 2: Uncovering social ties (A.Gruzd)
4. Sense of Community in Online Communities (A.Gruzd)
5. Digital divides and the impact of online networks on civic engagement (I.Talmud)
6. Online friendship and maintenance (I.Talmud)

Computer Practice (B.Lind & A.Hanna):

1. GUI-based online data collection (NodeXL, Gephi, etc)
2. API-based online data collection (with Python)
3. Online data collection through web-scraping (with Python)
4. R practice 1: Introduction to R and its network analysis packages. Review the types of grpahs and their data structures for input.
5. R practice 2: Common nodal, subgraph, and graph-level measurements
6. R practice 3: Random graphs, theoretical assumptions, and their purposes for baseline distributions as well as modeling
7. R practice 4: Ego-centric data analyses and generalization through ERGM

Day-to-day course schedule