Quantitative empirical social research has traditionally used two main types of data: First, survey data, in which population samples were examined either once (cross-sectionally) or several times (longitudinally) using questionnaires. Survey data have for a long time been the sole source of data for research on attitudes, preferences, and life situations. Second, process-generated and administrative data collected within the framework of official statistics have been analyzed, usually at a slow pace and with many access limitations. As a result of ongoing digitalization, a lot of data is accumulating online that can also provide increasingly comprehensive information about public opinion as well as people’s living conditions and behavior. These data can be used for answering central sociological research questions. This refers not only to social media data, but also to usage or observational data as collected via smartphones or other measurement devices. In the social sciences, a new field of research ("computational social sciences") is currently developing that explores the possibilities of using these data, including the question of their methodological quality. In this seminar, the development of these new data spaces for social science research will be presented and discussed using selected examples. This will include hands-on practice sessions, where participants can gain an impression of the benefits and limitations of such digital data. close