Faculties and centres
1. INTRODUCTION: graphs and their properties, degree distributions, graph measures, centrality.
2. RANDOM NETWORKS: Erdos-Reny, general random graphs, random network formation, the emergence of network properties.
3. GAMES IN NETWORKS: complete and incomplete information
4. INFORMATION IN SOCIAL NETWORKS. Difussion and contagion. Information transmission. Imperfect information and the formation of expectations. Learning in networks.
5. APPLICATIONS AND EMPIRICAL CONSIDERATIONS. Citation and scientific networks, applications to crime, empirical estimation and endogeneity.
General Competences (CG)
Specific Competences (CE)
This course is designed with the two main purposes of giving students a systematic grounding in Social Networks and preparing them to use network economic models in their own research.