(Introduction to) Network Analysis 2023/24

Week Date Lectures Labs Coursework
1 Feb 19th Networks motivation, graph theory vs network science, graphology Recitation on NetworkX library, Pajek format etc.
2 Feb 26th Networkology, network representations & data, Erdos-Renyi model Network representations, basic network algorithms Homework #1 out
3 Mar 4th Configuration model, small-world networks & model, scale-free networks Advanced network algorithms, random graph models
4 Mar 11th Scale-free networks & preferential attachment models, course projects Small-world & scale-free models, graphs vs networks
5 Mar 18th Node position & measures of centrality, link analysis algorithms Measures of node centrality, PageRank algorithm
6 Mar 25th Link importance & measures of bridging, network perspectives, some applications Link betweenness, node similarity, errors & attacks Homework #1 due
7 Apr 1st Community structure, community detection & graph partitioning Community structure & detection, coursework consultations Homework #2 out
8 Apr 8th Node equivalence & blockmodeling, core-periphery structure Blockmodeling & block models, \(k\)-core network decomposition
9 Apr 15th / /
10 Apr 22nd Node mixing in networks, fragments & frequent subgraphs Node mixing by (not) degree, graphlet degrees
11 Apr 29th / / Homework #2 due
12 May 6th Network sampling & comparison, backbones & (convex) skeletons Random-walk sampling, network comparison
13 May 13th Node layout & network visualization, course challenges, some applications Wiring diagram & block models, coursework consultations
14 May 20th Network inference & link prediction, graph machine learning Node embeddings & classification, link prediction
15 May 27th Selected applications & research topics, tentative invited talks (Q&A) Course project due