Coursebook for “Complessita’ nei Sistemi Sociali”

Laurea Magistrale in Fisica Dei Sistemi Complessi A.A. 2023/24

Lecturers: Maxime Lucas, Lorezo Dall’Amico

Course overview

Introduction

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

Network analysis

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

Dynamical processes

• 9. Random walks
• 10. Synchronization

Hypergraphs

• 11. Getting started with XGI
• 12. Case study: sync

Temporal graphs

• 13. Temporal networks
• 14. Source code

Epidemics on networks

• 15. Epidemics on networks
• 16. Source code

Graph Fourier transform

• 17. Graph Fourier transform
• 18. Source code

Community Detection

• 19. Community detection
• 20. Source code

Node2Vec

• 21. Node2Vec

Slides

• Lesson 1: Course Intro

• Lesson 2: Intro to networks

• Lesson 3: Random models

• Lesson 4: Growing models and assortativity

• Lesson 5: Percolation and random walks

• Lesson 6: Multilayer, hypergraphs, and synchronization

Notes

• Lesson 7: Temporal graphs

• Lesson 8: Epidemics on networks

• Lesson 9: Cavity method

• Lesson 11: Graph Fourier transform

• Lesson 10, 12, 13: Community detection

• Lesson 14 Node2Vec