David Garcia, 2022
Welcome to the online materials for Computational Modelling of Social Systems. In this course, you will learn how to formulate and analyze computational models of social systems, in particular to study social interaction and the behavior of large groups of people and whole societiess. The course integrates contentz about social dynamics and analytic tools to understand the complex behavior of social systems. After this course, you will acquire programming skills to implement, simulate, and visualize these models.
I am the Professor for Computational Behavioral and Social Sciences the Graz University of Technology, where I lead the Computational Social Science Lab. I am also group leader at the Medical University of Vienna and at the Complexity Science Hub Vienna. My background is Computer Science but I worked my whole career with psychologists, sociologists and physicists to learn new ways to understand human behavior. I got my PhD from ETH Zurich in 2012 and a habilitation in 2018, starting to work as full professor TU Graz in 2020. To learn more about my research, check my publications. I teach this course in collaboration with the two postdoctoral researcher in the Computational Social Science Lab Dr. Petar Jerčić and Dr. Jana Lasser.
The course is organized in 12 lectures grouped together in 4 blocks, plus two sessions in the end for project presentations. The course contains lectures and exercises in python to apply what you learned in the lecture. The online materials do not contain the solutions to the exercises, but if you are stuck or want to start from an easier point, in the github folder of the exercise you can find a version of the exercise with hints. We will add links to materials and readings a few days before each session.
(Please install Jupyter Notebook before the tutorial sessions takes place, where we can provide help with the installation if something goes wrong.) The easiest way is using the Anaconda distribution, since it is well supported and maintained.
No class between 9.04.2022 and 23.04.2022: Easter holidays
No class on 26.05.2022: Ascension day
Modelling epidemics: the SEIRX model [Slides] (06.02.2022)
Lecture Q&A session [Slides] (09.06.2022)
Project guidance
No class on 16.06.2022: Corpus Christi
The course takes place on Thursdays at 16:15 (sharp), with a lecture followed by an exercise session. The first session of the course will take place in room HS F (Kopernicusgasse 24) with live streaming over Webex (see TeachCenter for the link). From the second week of the course, the course will take place in HS i7 (Inffeldgasse) and streaming will take place through the standard TU Graz streaming system.
The semester starts with a yellow light, so we will start in hybrid mode with limited occupancy in person. When attending in person, proof of 2G status might be required and seating space is limited depending on varying policies. Seating will be given in a first-come-first-served basis each session and students that do not fit will have to follow the lecture online from another place.
There is an extra online exercise support group on Wednesdays at 13:00 (sharp). Check TeachCenter for the webex link.
The assessment for the course is based on four components:
You can find more information about the project presentations and reports, including deadlines, in the projects guide. You can also find some guidance and recommendations in the slides of the project support session.
Graded exercises need to be submitted on teach center by the deadline (end of day in Graz time). We will provide solution files for ungraded exercises for you to check your progress. Nevertheless, we expect to see in your projects the techniques covered in the exercises, both graded and ungraded.