Structure and Dynamics of Complex Networks

Term: 
Winter
Credits: 
2.0
Course Description: 

Course code: CNSC 6007

Description

The aim of this course is to deepen the knowledge of students in networks science, to get acquainted with some important specific problems at the frontier of research and get skills to work with present day literature.

The bulk of the course will be provided in lectures. There will be discussions of the tasks and the final projects will be presented by the students in a seminar form. Students are encouraged to consult the recommended literature.

There will be two assignments. Both assignments will consist of home prepared work. The students will have to prepare a project work and present in the last class.

Course schedule

Week 1st lecture Comments
1 Introduction, block modelling
2 Community detection revisited
3 Core-periphery structures
4 Hierarchies Assignment 1
5 Optimization
6 Synchronization
7 Multiplex networks Assignment 2 (mid-term)
8 Link formation and prediction
9 Search on networks
10 Spreading phenomena
11 Cascades
12 Project presentation

Suggested reading

Books:

M.E.J. Newman: Networks – An Introduction (Oxford UP, 2010)

A. Barrat, M. Barthélemy and A. Vespignani: Dynamical Processes on Complex Networks (Cambridge UP, 2008)

D. Easley and J. Kleinberg: Networks, Crowds and Markets (Cambridge UP, 2010)

Articles:

S. Fortunato: Community detection in graphs. Physics Reports 486, 75–174 (2010)

S. Fortunato and D. Hric: Community detection in networks: A user guide. Physics Reports 659, 1–44 (2016)

M. P. Rombach et al.: Core-periphery structure in networks, SIAM J. App. Math. 74, 167 (2014)

B. Corominas-Murtra et al: On the origins of hierarchy in complex networks, PNAS 110, 13316 (2013)

S. Boccaletti et al. Structure and Dynamics of Multilayer Networks, Physics Reports 544, 1, (2014)

M. Kivela et al. Multilayer networks, Journal of Complex Networks 2, 203 (2014)

G. Kossinets and D. Watts: Origins of homophily in evolving networks, Amer. J. Sociol. 115, 405 (2009)

D. Liben-Nowell and J. Kleinberg: The link-prediction problem for social networks, J. Amer. Soc. Information, Sci. and Technol. 58, 1019 (2007)

R. Pastor-Satorras et al.: Epidemic processes on complex networks, Rev. Mod. Phys. 87, 925 (2015)

Teaching format

The bulk of the course will be provided in lectures. Every student will have the task to present an article to be selected in 10-15 minutes. There will be discussions of the tasks and the final projects will be presented by the students in a seminar form. Students are encouraged to consult the recommended literature.

E-learning

The course has an e-learning site where the materials about the lectures, assignments, etc. will be posted. It also serves for communication.

Learning Outcomes: 

By successfully absolving the course the students will be able to:

- get orientation in the present day literature in network science;

- get insight into specific problems and work on them;

- be able to identify specific research problems in network science and get access to tools needed to solve them.

Assessment: 
There will be two assignments. Both assignments will consist of home prepared work. The students will have to prepare a project work and present in the last class.
  • Assignments (assignment 1: 10%, assignment 2: 20%)
  • Article presentation (20%)
  • Final project (40%)
  • Teacher evaluation (10%)
Prerequisites: 

Absolving “Fundamental Ideas in Network Science” is recommended. Basic knowledge of programming is required.