Coursebook for “Complessita’ nei Sistemi Sociali”

Laurea Magistrale in Fisica Dei Sistemi Complessi A.A. 2022/23

Lecturers: Giovanni Petri, Maxime Lucas

Course overview

Introduction

• 1. Python is easy :)
• 2. Basic network import and representation

Network analysis

• 3. How to fit a power law distribution
• 4. Basics of network analysis
• 5. Erdos-Renyi random networks
• 6. Network assortativity
• 7. Network robustness

Dynamical processes

• 8. Random walks
• 9. Epidemic modeling, deterministic and stochastic models
• 10. Epidemics on networks
• 11. Synchronization

Social contagion

• 12. Axelrod model
• 13. Higher-order Naming Game
• 14. Simplagion Model

Temporal Networks

• 15. Epidemics on temporal networks
• 16. Temporal networks libraries
• 17. Inferring biological phases by clustering snapshots

Community detection

• 18. Community detection
• 19. Comparing Partitions

Hypergraphs

• 20. Getting started with XGI
• 21. Case study: sync