CSS (computational social science) is located at the interface of social science and computer science. Social phenomena are therefore the main focus of our research. They are, however, analyzed using "new" data types.
In particular, this includes process-generated data, such as minutes of plenary proceedings, scientific texts and collaborations, or messages on social media channels (such as tweets). Methodologically, CSS combines inferential statistics with iterative calculation rules (e.g. algorithms), or Bayesian probability classifications. These can then be used to identify topics within large quantities of texts, to predict economic growth, or to investigate the coevolution of social relationships and attributes.
In addition to data issues and the intertwined development of innovative methods, our group also focuses on their "social science fit". This means, we are commited to ensuring the validity and reliability of data and also want to ensure the theoretical applicability of the methods.