The course is organized in 6 lectures. Each lecture will take place in room LT2 from 9:30am to 12:30pm. Subscribe to the official calendar of the course and get all schedule updates.

Tuesday 1st September

LECTURE 1: CENTRALITY MEASURES

Introduction to the course. Social network analysis and the importance of being central. Degree and eigenvector centrality. Betweenness, Closeness and Delta centrality. Group centrality. MCA: an application to urban design and planning.

Thursday 3rd September

LECTURE 2: RANDOM GRAPHS

Graph theory. Euler theorem and the bridges of Konigsberg. Erdős–Rényi random graphs models. Degree distribution. Trees, cycles and complete subgraphs. Giant connected component. Scientific collaboration networks.

Friday 4th September

LECTURE 3: SCALE-FREE GRAPHS

Random graphs with a given degree sequence. The Molloy and Reed criterion. Citation networks and the linear preferential attachment. The Barabási-Albert model. Other models of growing graphs. 

Monday 7th September

LECTURE 4: PERCOLATION

The Achille's heel of the Internet. Percolation theory. Critical threshold and critical exponents. The theory of tolerance to random failures and to intentional attacks. 

Tuesday 8th September

LECTURE 5: RANDOM WALKS

P2P networks. Random walks on graphs. The Markov-chain formalism.  Search time and bandwidth.  Searching the Web. Google and the PageRank algorithm.

Thursday 10th September

LECTURE 6: DISEASE SPREADING

Disease spreading. Compartmental models. SIR and SIS model. Homogeneous mixing hypothesis. Epidemic threshold in scale-free networks. Immunization strategies.