Social Networks

Course Description

The course offers students the opportunity to acquire knowledge and skills in the interdisciplinary field of social networks. Social networks are not only the most popular service based on the Internet infrastructure, but also a true global phenomenon that greatly affects the modern way of life and doing business. Students will acquire theoretical knowledge about the structure and processes in social networks, as well as practical knowledge and skills about application of social networks or achieving individual user or business goals.

Learning Outcomes

  1. explain the role and importance of social networks in today's society
  2. distinguish between social networks with respect to their structural properties and processes that occur in them
  3. differentiate methods for analysis of social networks
  4. use appropriate tools for analysis of social networks
  5. apply social networks to achieve individual user or business goals
  6. design information and communication systems based on social networks

Forms of Teaching

Lectures

Seminars and workshops

Independent assignments

Laboratory

Week by Week Schedule

  1. Social networks overview, Example social network platforms
  2. Structure of social network graphs, Social network analysis
  3. Structure of social network graphs, Social network analysis
  4. Clustering, Centrality, Spectral properties of adjacency matrix, Degree distributions, Degree correlations, Community structure diameter
  5. Complex networks: scale-free networks, small-world networks
  6. Algorithms for computing degree distributions and clustering coefficients, Extremal paths and breadth-first search, maximum flows and minimum cuts, spanning trees, Graph partitioning, community detection, Search on networks, Inference of network structure
  7. Algorithms for computing degree distributions and clustering coefficients, Extremal paths and breadth-first search, maximum flows and minimum cuts, spanning trees, Graph partitioning, community detection, Search on networks, Inference of network structure
  8. Midterm exam
  9. Challenges in user privacy: context-aware services and services based on social networks, Social networks security
  10. Internet user profiling; Brand profiling
  11. Social networking; Case studies of Facebook, Twitter, and LinkedIn
  12. Social networking; Case studies of Facebook, Twitter, and LinkedIn
  13. Social networking; Case studies of Facebook, Twitter, and LinkedIn
  14. Advanced information and communication services based on social networks, Programming based on social networking sites
  15. Final exam

Study Programmes

University graduate
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Electronics (profile)
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Information and Communication Engineering (profile)
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Literature

(.), Social and Economic Networks,
(.), Dynamical Processes on Complex Networks,
(.), Cases on Web 2.0 in Developing Countries: Studies on Implementation, Application, and Use,
(.), Analyzing the Social Web,
(.), Computational Social Networks: Mining and Visualization,

Associate Lecturers

Laboratory exercises

For students

General

ID 222558
  Winter semester
5 ECTS
L3 English Level
L1 e-Learning
30 Lectures
5 Seminar
13 Laboratory exercises