PostGraduate Course : Network Science for Data Analytics

General Information


Networks appear in practically all environments of human life. Humans organize themselves naturally by building networks (social, economic, biological), our families and neighborhoods are important networks for us. Organizations function by building complex, interconnected networks of business and financial associations. Public health is promoted through associations and coalitions of governments. Nations are connected to each other through migration systems, trade etc. On the other hand, nonhuman networks exist almost anywhere you look, genes and proteins interact with each other through complex biological networks, likewise, the human brain is a complex network. Social and scientific progress is driven by a process of diffusion of innovation whereby Information spreads through connected social systems. Network Science offers a common language and several methods through which different disciplines interact and try to solve common problems, It offers a general and powerful methodology for modeling and representing simple and complex interactions. This course is focused on studying the general conceptual and applied framework of network science. Fundamental concepts , commonly used and state-of-the-art methods will be studied. Major topics include, centrality measures of networks, models , some basic concepts of statistical and machine learning methods, and their applications in context; likewise, real world problem solving will be illustrated by showing various examples in a practical approach.

Course Objectives

Grading

Class Resources

Orientation Session



Weekly Schedule




Description Slides Jupyter Notebooks Additional material
Week 1 February 7 Introduction to Data Science Introduction to data Science Chapter 1 from Easley and Kleinberg: Overview
Week 2 February 14 Introduction to Network Science
New!!! Slides What is Network Science?( Zip)
Slides Basic Network Concepts(zip) 		Filippo Menczer:
Network Basic Concepts Part 1
Network Basic Concepts Part 2
Erika Legara :
Introduction to Network Analysis 		Videos: Master Class Video: The power of Network Science
Video Basic Network Concepts: Andrew Beveridge
Week 3 February 21 Local Measures on Networks

New!!! Slides Basic Concepts of graphs
New!!! There Central Quantities Networkx (Google Colab)
New!!! Slides Centrality Measures

Filippo Menczer
Centrality Measures
Erika Legara:
Centrality Measures 		Reading Material:
Simple properties of Graphs
Centralities of a Graph
Videos:
Andrew Beveridge Basic Centrality Measures (15 min)
Algebraic Centrality Measures (11 min)
Case studies:
0. In video: Centrality in a Dolphin Network (3 min)
1. Local: Local Measures Medici Family
2. Global Global Measures Edward Platt
Week 4 February 28 Global Measures of networks New!!! Slides Global Measures of a Network
Simple properties of Graphs
Centralities of a Graph
Videos:
Andrew Beveridge Basic Centrality Measures (15 min)
Algebraic Centrality Measures (11 min)
Case studies:
0. In video: Centrality in a Dolphin Network (3 min)

  1. Local: Local Measures Medici Family

  2. Global Global Measures Edward Platt
    Videos:
    Network Models:
    Excellent!!! The Promise of Network Science, 2017
    Erdos-Reny1 Model:
    Rand and Small World Networks Leskovec 26:45
    Random Networks Lada Adamic
    Watts-Strogatz Model:
    Small Worlds Melanie Mitchell
    Small World Networks Andrew Beveridge
    Small Worlds Verisatium
    Barabasi-Albert model:
    Scale Free Distrib Mel. Mitchell P1
    Scale Free Distrib Mel. Mitchell P2
    Preferential Model Katherine Carl
    Generative Models:
    Leskovec
Week 5 March 6 Network Models Part 1 !!New!!! Slides Network Models
Filippo Menczer :
Network Models
Erika Legara:
Network Models 		Reading material:
Filippo Menczer Network Models
Van Steen Random Models
Labs:
Models Netlogo Labs
Videos:
Network Models:
Excellent!!! The Promise of Network Science, 2017
Erdos-Reny1 Model:
Rand and Small World Networks Leskovec 26:45
Random Networks Lada Adamic
Watts-Strogatz Model:
Small Worlds Melanie Mitchell
Small World Networks Andrew Beveridge
Small Worlds Verisatium
Barabsi-Albert model:
Scale Free Distrib Mel. Mitchell P1
Scale Free Distrib Mel. Mitchell P2
Preferential Model Katherine Carl
Generative Models:
Leskovec
Week 6 March 13 Network Models part 2 Slides Network Models Erika Legara :
Exploring Social Distancing
Vaccination Strategies
 Reading material:
Michel Coscia Spreading Processes
Filippo Menczer Diffusion in Networks
Videos:
Diffusion:
Lada Adamic Proceses in Networks (12 min)
Social Networks diffusion
Network Diffusion and Contagion
Matthew Jackson Diffusion in Social and Economic Networks
Labs:
Difussion Netlogo Labs
Week 7 March 20 Diffusion and Vulnerabiliy Diffusion and Vulnerability Reading material:
To do
Videos:
Node Embeddings:
Katherine Carl Network Robustness
Network Robustness and Resilience
Labs:
Difussion Netlogo Labs
Holy Week
Week 8 April 3 Mini Project Presentations Expert Guest: Andy Dominguez Data Reading Material:

Mark Newman Assortativity
John Kleinberg Mesage Passing (to do)
Web Page Node Classification (to do)
Videos:
Classic Graph ML Tasks
Labs:
Robustness Netlogo Labs

Labs:

Netlogo Lab Sancho
Week 9 April 10 Communities in Networks ¡¡¡¡New!!!! Slides Homophily and Communities
Slides Communities Filippo Menczer
Slides Communities Leskovec 		Filippo Menczer :
Partitions and Communities 		Reading material:
Filippo Menczer Communities
Videos:
Leskovec Community Structure in Networks 2019
Leskovec Community Detection in Networks 2021
Leskovec Network Communities 22 min 2021
Jure Leskovec Louvain Algorithm
Jure Leskovec Detecting Overlapping Communities
Beveridge: Modulatity and the Louvain Method
Labs:
Netlogo Lab Sancho
Week 10 April 17 Project Prototype Presentations Data Data Data
Week 11 April 24 Deep Learning with Graphs Part One Data Data Data
Week 12 May 8 Deep learning with graphs Part Two Data Data Data
Week 13 May 10 Final Project Presentations — — —









Projects

Projects Other Universities

Projects Jure Leskovec Course 2009