194.050 Social Network Analysis
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2023W, VU, 2.0h, 3.0EC


  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise
  • Format: Hybrid

Learning outcomes

After successful completion of the course, students are able to

  • apply theoretical concepts and methods to practical tasks of social network analysis,
  • analyze networked data, and
  • properly assess the results of a social network analysis and draw appropriate conclusions.

Subject of course

Topics, which are covered in this course, include basic concepts in graph theory, important measures and metrics in network theory, community detection, social network analysis, the small-world experiment, the structure of the World Wide Web, the large-scale structure of networks, and processes on networks.

Teaching methods

The content of the course is presented in lectures and developed in accompanying exercises by students. There is also a group project.

Mode of examination


Additional information

Note: The course starts on October 12th, 2023.

Please only use the following e-mail address to contact the lecturers: sna-ws23@ec.tuwien.ac.at

Note: Students in a Bachelor programme can only participate if they have at least 162 ECTS.

Workload for students (in hours):

  • Lecture Time: 15
  • Project Work: 35
  • Preparation for Test: 25
  • Sum: 75



Course dates

Thu10:00 - 12:0005.10.2023 - 25.01.2024EI 8 Pötzl HS - QUER Lecture
Thu10:00 - 12:0025.01.2024EI 7 Hörsaal - ETIT Test
Social Network Analysis - Single appointments
Thu05.10.202310:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu12.10.202310:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu19.10.202310:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu09.11.202310:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu16.11.202310:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu23.11.202310:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu30.11.202310:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu07.12.202310:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu14.12.202310:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu21.12.202310:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu11.01.202410:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu18.01.202410:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu25.01.202410:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu25.01.202410:00 - 12:00EI 7 Hörsaal - ETIT Test

Examination modalities

The assessment is based on a written test, exercises and a group project.

Course registration

Begin End Deregistration end
11.09.2023 09:00 13.10.2023 23:59 31.10.2023 23:59


Study CodeObligationSemesterPrecon.Info
066 645 Data Science Not specified
066 926 Business Informatics Mandatory elective


The lecture slides will be available on the Web.


Aggarwal, C. C. (Ed.): Social Network Data Analytics. Springer, 2011.

Barabási, A.-L.: Network Science. E-Book, Work in Progress. http://barabasilab.neu.edu/networksciencebook/

Brandes, U., Erlebach, T.: Network analysis : methodological foundations. Springer, 2005.

Easley, D., Kleinberg, J.: Networks, crowds, and markets: reasoning about a highly connected world. Cambridge Univ. Press, 2010. http://www.cs.cornell.edu/home/kleinber/networks-book/

Hanneman, R. A., Riddle, M.: Introduction to social network methods. University of California, Riverside, 2005. http://www.faculty.ucr.edu/~hanneman/nettext/

Hansen, D. L., Shneiderman, B., Smith, M.. A.: Analyzing social media networks with NodeXL: insights from a connected world. Morgan Kaufmann, 2011.

Monge, P. R., Contractor, N. S.: Theories of communication networks. Oxford University Press, 2003.

Newman, M. E. J.: Networks: an introduction. Oxford Univ. Press, 2011.

Previous knowledge

Basic Knowledge of Linear Algebra, Calculus and Statistics