(Introduction to) Network Analysis 2022/23

Week Date Lectures Labs Coursework
1 Feb 13th Networks motivation, graph theory vs network science, graphology /
2 Feb 20th Networkology, network representations & data, Erdos-Renyi model Recitation on NetworkX library, Pajek format etc. Homework #1 out
3 Feb 27th Configuration model, small-world networks & model, scale-free networks Network representations, basic network algorithms
4 Mar 6th Scale-free networks & preferential attachment models, some applications Advanced network algorithms, random graph models
5 Mar 13th / / Homework #1 due
6 Mar 20th Node position & measures of centrality, link analysis algorithms Small-world & scale-free models, graphs vs networks
7 Mar 27th Link importance & measures of bridging, perspectives & course projects Measures of node centrality, PageRank algorithm Homework #2 out
8 Apr 3th Community structure, community detection & graph partitioning Link betweenness, node similarity, errors & attacks
9 Apr 10th Node equivalence & blockmodeling, core-periphery structure (coursework consultations)
10 Apr 17th Node mixing in networks, fragments & frequent subgraphs Community detection, blockmodeling with block models Homework #2 due
11 Apr 24th / \(k\)-core decomposition, node mixing by (not) degree
12 May 1st Network sampling & comparison, backbones & skeletons (coursework consultations)
13 May 8th Node layout & network visualization, network epidemics, some applications Graphlet degrees, random-walk sampling, network comparison
14 May 15th Network inference & link prediction, graph machine learning Wiring diagram & block models, PageRank & betweenness challenge
15 May 22nd Applications of network analysis, (tentative) invited talks Node embeddings & classification, link prediction Course project due
16 May 29th / (Q&A)