Digital and networked media permeate almost all areas of life. The analysis of digital traces – i.e. social media postings, audiovisual content, but also app and web tracking data – has enormous potential for understanding social phenomena. The same applies to the use of research software to survey media and data practices. However, both also pose technical, methodological and epistemological challenges that must be overcome in order to answer research questions and draw scientific conclusions.

At the ZeMKI, standardised methods as well as qualitative digital and computer-based methods are used and further developed in research and teaching to explore questions of digitalisation, datafication and profound mediatisation (“computational communication research”). This includes the use of open source and commercial research software (e.g. for the collection of media diaries or media repertoire sorting) as well as command line-based computer interfaces and programming languages such as R and Python. This also includes the use of computational observation and coding methods (e.g. “eye tracking”, automated facial action coding, qualitative coding), the use of mobile surveys (“experience sampling”), network analyses supported by crawlers or based on programming interfaces (APIs), text mining, the use of machine learning methods for the evaluation of image content and methods of digital ethnography.

Guiding questions of the competence area Digital Methods in Context include: Which combinations of digital and established empirical methods complement each other in a meaningful way? How can we ensure that theory-based questions – rather than the mere availability of data – guide our insights into new phenomena? What teaching methods and curricula are appropriate for imparting the necessary methodological skills to students and researchers? How can the increasing automation of communication via “communicative AI” (bots, voice-based digital assistants, etc.) be explored?