1. S OCIAL N ETWORK A NALYSIS F OR D UMMIES Y ANNE B ROUX DH S UMMER S CHOOL L EUVEN, S EPTEMBER 8 2015

2. T ERMINOLOGY

3. Useful sources A.-L. B ARABÁSI, Linked: The Science of Networks (Cambridge, 2002) S. B ORGATTI et al., Analyzing Social Networks (L.A., 2013) Y. B ROUX & S. V ANBESELAERE, Six Degrees of Spaghetti Monsters (spaghetti-os.blogspot.com)

5. Basics Node (vertex) Edge (tie) – Undirected – Directed – Weighted (valued) Degree: how many edges to a node – Undirected: count edges – Directed: indegree vs outdegree A B C D E F

6. D ATA MANAGEMENT

7. Adjacency matrix Symmetric, binary e.g. who knows who Symmetric, weighted e.g. distance between places

8. Adjacency matrix Asymmetric, binary e.g. choose 3 friends to sit with Asymmetric, weighted e.g. number of emails sent to colleagues

9. One-mode vs two-mode 1-mode: direct ties between actors (= adjacency matrix) 2-mode: ties between different entities (= affiliation matrix)

10. Adjacency vs attribute matrix Adjacency matrix: only records ties between nodes Attribute matrix: each column is different attribute of the nodes (gender, role, ethnicity, status, …) = ‘nodelist’ (vs ‘edgelist’)

11. Attribute matrix (nodelist)