Kaisa_2012_3_photo by Veikko Somerpuro

The course combines both theoretical knowledge about network analysis and hands-on skills on how to conduct such analysis.

This course focus both on the theory and practice of network analysis, perceived broadly as an analysis paradigm to understand interactions between people (social networks), relationships between words in the text (text networks) and so on. As this course has both lectures on more methodological nature and hands-on-laboratories, you should have a working knowledge of R or Python before the first class.

7.3.2019 at 09:00 - 13.5.2019 at 23:59



The course will show you both how to use descriptive tools (key measurements and plots) as well as analytical approaches (random graph models, random walks, hypothesis testing) in network analysis. Beyond that, we focus on how to see phenomena through the lenses of networks and consider advanced models of network analysis, like multilayered and temporal networks.

Mon 13.5.2019
16:15 - 17:45
Wed 15.5.2019
16:15 - 17:45
Thu 16.5.2019
16:15 - 17:45
Tue 21.5.2019
16:15 - 17:45
Mon 27.5.2019
16:15 - 17:45
Tue 28.5.2019
16:15 - 17:45
Wed 29.5.2019
16:15 - 17:45


Conduct of the course

Each class will have two separate components: the lecture will focus on the conceptual dimension of network analysis, including pre-reading assignments, classroom discussions and some slides. This will take about 45 minutes. The class is then followed by the laboratory part, where students will work through learning activities, including example codes and expanded questions.

Based on the skills gained from the lectures, each student will write a final report where an empirical research question is explored using some analysis methods demonstrated during the classes. Students will be evaluated only based on the final report.