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Network Theory and Dynamic Systems

Gespeichert von suwestcms am Di, 04/15/2014 - 14:03

Lecture & Tutorial (3+1)

Lecturer

Teaching assistant

The lecture and tutorials will be given in English.

Competencies to be acquired

The student should become enabled to understand the structure and the dynamics of network models and how to apply them to structures of artefacts and human behaviors in the World Wide Web.

Time and locations

NTDS Lecture Mo, 10 - 12, Room E 524 Prof. Dr. Steffen Staab / Dr. Christoph Ringelstein
NTDS Lecture Di, 14 - 15, Room A 120 Prof. Dr. Steffen Staab / Dr. Christoph Ringelstein
NTDS Tutorial Di, 15 - 16, Room A 120 Julia Perl 
The programming exercises will be implemented in the free software
Octave. For the first exercise on Tuesday, 17th April, you should have installed Octave ( http://www.gnu.org/software/octave/download.html ), so we can start with an introduction to the software.

Octave tutorial:
http://www-mdp.eng.cam.ac.uk/web/CD/engapps/octave/octavetut.pdf

 

Lectures

Date Lecturer Topic Slides
16.4. Dr. Ringelstein Introduction Set 1
22.4. Prof. Staab

Introduction pt. 2

 Set 2

22./23.4.

  Prof. Staab

Strong and Weak Ties

 Set 3
30.4. Prof. Staab Networks in their Surrounding Contex (added note about false graphics) PDF
7.5. Prof. Staab Positive and Negative Relationships PDF
8.5. Prof. Staab Game Theory PDF
14.5. Prof. Staab Game Theory: Mixed Strategies PDF
15.5. Prof. Staab Information Networks PDF
21.5. Prof. Staab Link Analysis and Web Search PDF
22.5. Dr. Ringelstein Link Prediction PDF
4.5. Prof. Staab Link Prediction 2 PDF
5.6. Dr. Ringelstein Spectral Clustering and Graph Drawing PDF
11.6. Prof. Staab Sponsored Search Markets PDF
12.6. Prof. Staab Information Cascades PDF
18.6. Prof. Staab Bayes  PDF
19.6. Prof. Staab Network Effects PDF
25.6. Dr. Ringelstein Power Law and Rich-get-richer PDF
26.6. Dr. Ringelstein Long Tail PDF
2.7. Prof. Staab Diffusion Networks PDF
3.7. Prof. Staab Small World PDF
9.7. Prof. Staab Markets PDF
10.7. Prof. Staab Voting PDF

Assignments 

No. Date Assignment Due date Sample solution
  18.4. Assignment 1 23.4.  Solution 1
2 24.4. Assignment 2  7.5.  
3 9.5. Assignment 3 14.5.  Solution 3
4 16.5. Assignment 4 21.5.  
5 28.5.

Assignment 5,

datasets

 11.06  
6 6.6.

Assignment 6

datsets

 11.06.  
7 12.6.

Assignment 7

datasets

 18.06.  
8 19.06.

Assignment 8

datasets

 02.07.  
9 03.07.

Assignment 9

datasets

 16.07.  

Credits are earned by passing the exam.

You may earn additional points counting towards the exam by completing the excercise assignments consisting of theoretical and practical excercises.

The assignments sum up to 90 points (10 points pro assignment)

AP >= 90% Total AP => 0.6 points improvement

AP >= 75% Total AP => 0.3 points improvement

AP - Assignment points

You should actively participate in the excercise group. Each student has to present at least 2 exercises in the backboard during the semester.

Contents

1. Graph Theory and Social Networks

    a. Paths

    b. Core network measures

    c. Strong and weak ties

    d. Homophily and link prediction

    e. Taxonomy of network types

2. Game Theory

    a. Definition of a game

    b. Best responses and Nash equilibrium

    c. Mixed strategies

    d. Pareto and Social Optimality

    (e. Modeling network traffic using game theory)

    (f. Tragedy of the commons)

3. Information Networks and the World Wide Web

    a. Structure of the Web

    b. Link analysis

    c. Sponsored search markets

4. Network dynamics: Population models

    a. Information cascades

    b. Economy with/without network effects

    c. Stability, Instability and Tipping points

    d. Power Laws and rich-get-richer phenomena

    e. Long tail

5. Network dynamics: Structural models

    a. Diffusion

    b. Small-world

    c. Epidemics

6. Group decision making

    a. Different voting schemes

Readings