Network Science and Applications

Course Description: 
Level:  Doctoral
Course Status:  Elective

Full description

Background and overall aim of the course

Introduces network science and the set of tools used to understand complex networks emerging in social and economic systems. Focuses on the empirical study of real networks, with examples from computer science (World Wide Web, Internet), social systems (e-mail, friendship networks), political systems (voting patterns, social networks). Shows the organizing principles that govern the emergence of networks and the set of tools necessary to characterize, model and visualize them.


  1. Networks: why do we care?
  2. The Random Worldview Random Networks Small world property
  3. Scale-free property
  4. Network Evolution
  5. Competition in networks - the role of fitness Robustness and failures in networks
  6. Communities
  7. Degree correlation (assortativity)
  8. Motifs/Sub-graphs
  9. Weighted Networks
  10. Spreading of ideas, viruses on networks.

Planned weekly schedule

Week 1:

Introduction (Ch1 of Network Science)

20 minutes: discuss the research projects.

Graph Theory (Ch2 of Network Science)

Hand out the network dataset for Homework 1.

20 min: discuss research project.

Random Network Model (Ch 3 of Network Science)

20 min: discuss research project.

Week 2:

Visualization/Software (Carl)

20 min: discuss research project.

Movie NightConnected by Annamaria Talas, Auditorium 19:00-20:30.

Scale-free property (Ch4 of Network Science)

20 min: discuss research project.

Evolving Networks (Ch5 of Network Science)

20 min: discuss research project.

Week 3:

Carl Office Hour

Preliminary Project Presentations

5 min/max. 5 slides.

Before class: Return Homework 1 (class network analysis)

Printout + email.

Weighted Networks/or Communities

20 min: discuss research project.

Network Robustness/Epidemic Phenomena/Assortativity/Hierarchy

Homework 2 is due (wiki). On Wiki page/email.

20 min: discuss research project.

Week 4:

Final Project Presentation

CEU auditorium

15 min/max 15 slides.

Other useful info:


Texbook: Network Science:

Chs. 1-3 are available at

Chs. 4-5 are available at the course webpage.

See also:  (a more extensive version  of the slides).

Contact us:

Carl, (Office: Nador utca 11, room 611),

Laszlo, (Office:  Nador utca 11, room 609)

We will create a google mailing list for the class, and invite everyone.

Learning Outcomes: 

The goal of the class is to develop analytical skills useful for the understanding the emergence, characterization and analysis of networks. Students are expected to acquire working knowledge of network analysis and visualization tools.


During the course students will be asked to solve the problems. They can handle the solution in written or electronic form. There will be a research project, performed in small interdisciplinary groups, that will require data collection, visualization, and analysis of a network of choice.


Assignment 1: Network analysis (20% of grade)

by email and print copy.

(network will be handed out on Class 2,).

Assignment 2: Wikipidia Article (20% of grade)

by email and print copy.

Final Project (60% of grade)

Goal: Collection and analysis of some real network data.

The project will be carried out in inter-departmental pairs of students. It consists of two phases:

Preliminary project presentation:

5 min/5 slides from each group. No grading, only feedback.

Final project presentation 

15 min/max 15 slides. Graded.