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.

2022W, 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

Please only use the following e-mail address to contact the lecturers: sna-lva@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 - 12:0006.10.2022 - 26.01.2023EI 8 Pötzl HS - QUER Lecture
Thu10:00 - 12:0026.01.2023Seminarraum Argentinierstrasse Exam
Social Network Analysis - Single appointments
Thu06.10.202210:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu13.10.202210:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu20.10.202210:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu27.10.202210:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu03.11.202210:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu10.11.202210:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu17.11.202210:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu24.11.202210:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu01.12.202210:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu15.12.202210:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu22.12.202210:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu12.01.202310:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu19.01.202310:00 - 12:00EI 8 Pötzl HS - QUER Lecture
Thu26.01.202310:00 - 12:00EI 8 Pötzl HS - QUER Exam
Thu26.01.202310:00 - 12:00Seminarraum Argentinierstrasse Exam

Examination modalities

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


DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Thu - 25.01.2024written19.12.2023 00:00 - 22.01.2024 23:59TISSExam - 1st date

Course registration

Begin End Deregistration end
13.09.2022 09:00 11.10.2022 23:59 30.10.2022 00:59


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