The Computational Social Systems (CSS) degree programme has been developed for students from the fields of business administration, sociology, psychology, law and computer science who would like to examine the effects of digitalisation in detail on their own and other disciplines, as well as analyse the resulting challenges and opportunities.
During your studies, you will receive an academic education in informatics topics such as data structures, algorithms, statistics, machine learning and data science and learn how to understand, classify and predict the behaviour of people using digital technologies. You will rely on this knowledge for the specific fields of application in your subject. Depending on the focus, you will become familiar with, for example, data-based business models, socio-technical issues, artificial life or robotics, or data law aspects.
In the basic module, you will learn more about the basics of computational social systems and obtain all the prior knowledge you will need for the subsequent specialisations. You will then specialise in one of four areas, depending on your previous education:
At the same time, you will work closely with students from other disciplines in various seminars and study projects and benefit from the expertise of internationally renowned lecturers.
Current research projects in the social sciences field, for example, are dedicated to the analysis of social media postings that were published immediately after critical events, such as natural disasters or terrorist attacks. Here at TU Graz, researchers use IT methods to better understand the behaviour of societal members in and after such situations.
Introduction to Computational Social Systems: You will receive an introduction to the subject areas of CSS and become familiar with various research methods used to analyse social systems. You will also learn how to use technologies and statistical methods to process, evaluate and interpret data.
Depending on your previous education, you will deepen your knowledge in one of the following areas of specialisation:
Business Analytics: You will become familiar with methods and technologies used to create data-based business models and decision support systems. In addition, you will learn, for example, how to set up a Business Intelligence Concept to solve business management problems or how to work with technologies to manage large amounts of data. At the same time, you will acquire knowledge in the field of computer science. Here, an emphasis is placed on statistical analyses, machine learning, modelling social systems and processing and evaluating data.
Societies, Technologies and Social Research: You will become familiar with the scientific discourse on the relationships among culture, social change and technology. You will also learn how to conduct an empirical research project, from the time you develop a research question to the time that you present the results, and how to apply various qualitative and quantitative research methods. You will address selected topics closely, such as the sociology of scientific knowledge, or analyse philosophical and socio-political perspectives of modern information technologies. You will acquire the ability to generate datasets and to process and evaluate them using machine-learning methods.
Human Factors: You will address core topics in cognitive psychology as well as current issues in decision research and analyse findings from behavioural and neuroscientific studies. You will conduct an empirical investigation on the psychology of human factors and can also address other research topics, such as artificial life and robotics, complex system modelling, or quantitative research methods. You become proficient in the use of concepts and technologies of human-computer interaction, such as wearable computer devices.
Law and Computer Science: You will become familiar with the theories of fundamental and human rights and with their application in the context of information technologies, based on the case law of the ECJ and the ECHR. You will address legal questions on data protection and IT products and learn how to conduct an analysis of user-generated data and social media by using statistical methods and machine learning. In addition, you will learn how to develop and implement the legal requirements for an IT system in practical projects.
In the Master's Degree Programme in Computational Social Systems, students acquire skills to understand the digital society and to seize the opportunities brought by the digital transformation. This program benefits from the unique interdisciplinary environment at TU Graz and the University of Graz. Based on an academic network that connects Computer Science with Psychology, Sociology, Law, and Business, this programme offers students an unprecedented combination of perspectives and skills.
I think it’s both necessary and brave to follow interdisciplinary paths when creating new degree programmes. Especially interdisciplinary teams have the courage to ask complex but exciting and highly relevant questions in an increasingly fragmented scientific world.
Plus, I think that the present degree programme offers qualified women the opportunity to make a technical impact in postgraduate studies, even if they completed a non-technical undergraduate degree programme, lowering the inhibition threshold by joining a group of like-minded people with prior knowledge in their respective subject areas.
The master's degree programme is offered jointly by TU Graz and the University of Graz. Students can thus benefit from the expertise offered by the two universities and the research network of internationally renowned lecturers, some of whom work at ETH Zurich and RWTH Aachen.
To be admitted to the degree programme, the following requirements must be fulfilled: the completion of a bachelor's degree in one of the following major subjects: Computer Science, Business Administration, Sociology, Psychology, or Law. At least 60 ECTS credits must be attributable to the respective subject area.
Additionally, you need to provide evidence of competence in the English language.
For the academic years 2022/23 and 2023/24 there will be no admission procedure.
You can go directly to the next step (2. Admission).
If you have already been admitted to a degree programme at TU Graz, or have studied at TU Graz before, please come to the Registrar's Office in person to complete your admission during the admission period.
As part of your admission to the degree programme, you announce your area of specialisation:
Graduates of this degree programme make a significant contribution to the further development of society by conducting research on socio-technical systems, developing future technologies and critically reflecting on their effects. As interdisciplinarily trained professionals, they apply their knowledge in industrial and service companies, areas of public administration, business and science.
They can work as