This course aims to provide insights into the structural analysis of social and information networks, particularly the World Wide Web. The participants should gain basic knowledge about network analysis methods and tools as well as their theoretical foundations.
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.
First Session: October 1st, 2019
On October 8th the course will not take place!
Note: Students in a Bachelor programme can only participate if they have at least 162 ECTS.
Workload for students (in hours):
- Lecture Time: 15
- Lab Assignments: 15
- Project Work: 20
- Preparation for Test: 25
- Sum: 75
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.
<p>The assessment is based on a written test, exercises and a group project.</p>
Basic Knowledge of Linear Algebra, Calculus and Statistics