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.

2021W, VU, 2.0h, 3.0EC
TUWEL

Course evaluation

Properties

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

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

Immanent

Additional information

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

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Tue10:00 - 12:0005.10.2021 - 25.01.2022 Zoom Meeting (LIVE)Lecture (online)
Social Network Analysis - Single appointments
DayDateTimeLocationDescription
Tue05.10.202110:00 - 12:00 Zoom MeetingLecture (online)
Tue12.10.202110:00 - 12:00 Zoom MeetingLecture (online)
Tue19.10.202110:00 - 12:00 Zoom MeetingLecture (online)
Tue09.11.202110:00 - 12:00 Zoom MeetingLecture (online)
Tue16.11.202110:00 - 12:00 Zoom MeetingLecture (online)
Tue23.11.202110:00 - 12:00 Zoom MeetingLecture (online)
Tue30.11.202110:00 - 12:00 Zoom MeetingLecture (online)
Tue07.12.202110:00 - 12:00 Zoom MeetingLecture (online)
Tue14.12.202110:00 - 12:00 Zoom MeetingLecture (online)
Tue11.01.202210:00 - 12:00 Zoom MeetingLecture (online)
Tue18.01.202210:00 - 12:00 Zoom MeetingLecture (online)
Tue25.01.202210:00 - 12:00 Zoom MeetingLecture (online)

Examination modalities

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

Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Tue - 25.01.2022written12.01.2022 00:00 - 23.01.2022 23:59TISSVU SNA WS2020 - First Test

Course registration

Begin End Deregistration end
14.09.2021 09:00 12.10.2021 23:59 31.10.2021 00:59

Curricula

Study CodeSemesterPrecon.Info
066 645 Data Science
066 926 Business Informatics

Literature

The lecture slides will be available on the Web.

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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

Language

English