Objectifs

In this course, we will cover basic mathematical tools to understand and analyze economic and social networks. First, you will learn how to represent networks (nodes, edges, paths, cycles, components of a network, degree and network density). Then, you will learn to measure networks (degree distribution, centrality, clustering). On our way, we will touch upon several economic applications, where understanding the network structure is crucial in understanding the social and economic outcomes.

Contenus

1. Basic concepts in graph theory.
2. Basic concepts in networks.
3. Strategic network formation.
4. Measuring networks: degree centrality, closeness centrality, betweenness centrality, eigenvector centrality, overall and average clustering, diameters, small worlds.
5. Random graphs.
6. Bipartite graphs and matching.

Références

Jackson, ”Social and Economic Networks”, Princeton University Press, 2008.

West, ”Introduction to Graph Theory”, Prentice Hall, 1996.

Evaluation

1ère tentative

Examen:

Ecrit 2h00 heures

Documentation:

Non autorisée

Calculatrice:

Autorisée avec restrictions

Evaluation:

Your final grade will be determined by a final exam, which is written and closed-book. The duration of the final exam is 2 hours.

Rattrapage

Examen:

Ecrit 2h00 heures

Documentation:

Non autorisée

Calculatrice:

Autorisée avec restrictions

Evaluation:

Written and closed-book.