This is a co-taught with the other members of the InfoLab Matteo Magnani and Christian Rohner .

Network Science is a very active and interdisciplinary research area aimed at studying physical, social and biological systems that can be modeled as sets of interconnected entities. The course covers the basics of network science, including social network analysis centrality measures (degree, betweenness, …), network properties (degree distribution, average path length, …), network models (Erdös-Renyi, small-world, preferential attachment), propagation (SI/SIR/SIS models, …), and the main network mining tasks (position/role detection, link prediction, community detection). All topics will be introduced in theory and practice, using the R system and different network analysis packages as hands-on exercises during the lectures. Then, students choose and review a set of important papers from different areas, selected by the teachers based on their importance in the field, to learn about advanced applications and developments.

The course covers the basics of network science, including centrality measures, network properties, network models, propagation, and the main network mining tasks.