Introduction to Network Analysis 2016/17

Week Date Lectures Labs Out Due Comment
1 Feb 21st Networks motivation, graph theory \(\rightarrow\) network science, course logistics / Homework #0
2 Feb 28th Graphology & networkology, network representations, formats & data Network representations, basic network algorithms Homework #0
3 Mar 7th Erdos-Renyi & configuration graph models, random graphs vs real networks Advanced network algorithms, random graph models Homework #1
4 Mar 14th Node position & measures of centrality, link analysis algorithms Measures of centrality, PageRank algorithm
5 Mar 21st / / Homework #1 CompleNet '17
6 Mar 28th Link importance & measures of bridging, small-world networks & model Homework #1 review, course project details Homework #2
7 Apr 4th Scale-free distributions & networks, preferential attachment models Small-world & scale-free models, graphs vs networks
8 Apr 11th Assortative & disassortative mixing, fragments & frequent subgraphs Node degree mixing, course project consultations Homework #2
9 Apr 18th Network community structure & detection, graph partitioning Network community detection, homework #2 review Homework #3
10 Apr 25th Equivalence, blockmodeling & block models, core-periphery structure Block models & \(k\)-cores, course project consultations
11 May 2nd / / Homework #3 Labour day
12 May 9th Network inference & prediction, network-based clustering, classification & regression Homework #3 review, course project proposals Project proposal
13 May 16th / / ARS '17
14 May 23rd Network collection & sampling, structural comparison,\(^§\) layout & visualization Random-walk sampling & Facebook, pegs & bands Project milestone
15 May 30th / Course project consultations
16 Jun 6th Fraud detection,\(^‡\) software engineering,\(^‡\) bibliometrics\(^‡\) & scientometrics\(^§\) Course project presentations Project deadline

\(^‡\)Conference talk    \(^§\)Conference poster