Universität Wien

250105 SE Complex Network Analysis Project (2023S)

4.00 ECTS (2.00 SWS), SPL 25 - Mathematik
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Friday 03.03. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 10.03. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 17.03. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 24.03. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 31.03. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 21.04. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 28.04. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 04.05. 11:00 - 13:00 Seminarraum 7 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 05.05. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 12.05. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 19.05. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 26.05. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 02.06. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 02.06. 13:15 - 16:30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Friday 09.06. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 16.06. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 23.06. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 30.06. 08:00 - 09:30 Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
  • Friday 07.07. 09:45 - 11:15 Seminarraum 9 Oskar-Morgenstern-Platz 1 2.Stock

Information

Aims, contents and method of the course

Aims: The course follows up on the lecture “Introduction to complex network analysis” held in the previous semester. The students will develop and conduct a project that further explores the theoretical concepts introduced in the lecture and applies them to a concrete dataset.

Content: In part 1, the students will map out and characterise a real world network. In part 2, the students will implement a didactic introduction of a basic network theory concept in a Virtual Reality platform. The progress will be presented and discussed through presentations throughout the semester.

Methods: Presentations and discussion of the project and the chosen approaches; independent work, implementation and documentation in exchange and discussion with a project advisor.

Assessment and permitted materials

The students will present the progress on their individual projects at seven separate meetings to the audience of the other participants. The two last meetings at the end of the semester are dedicated to the presentation of the final results. In addition, the implementation to be documented, for example if the form of python notebooks or a github repository.

Minimum requirements and assessment criteria

Minimum requirements: Presentations in front of the course participants; successful realization and implementation of the project; submission of project code and documentation.

Assessment criteria: All parts enter the grading, i.e. project presentations, realization, and documentation.

Examination topics

All topics relevant to the specific projects.

Reading list

This course is based on the lecture on complex network analysis from the last semester. The book Network Science by Albert-László Barabási (Cambridge University Press, 2016) serves as a reference. It can also be accessed online http://networksciencebook.com

Information on the VR platform can be found here: https://www.nature.com/articles/s41467-021-22570-w

Association in the course directory

MBIV

Last modified: Fr 30.06.2023 15:27