For evidence-based policymaking and its adequate public communication, an understanding of social discourses as well as their temporal development and dependence on societal and media events is necessary. Especially in dynamically developing fields of political action such as the Corona pandemic, migration, or climate policy, data from social media discourses offer opportunities to identify social trends, opinion patterns, and behavioral intentions.

The interdisciplinary project DiscourseData4Policy (DD4P) aims to use AI and machine learning methods to make social online discourses on Twitter understandable and usable to better understand dynamic interactions between social events, political measures, and their public acceptance. In this context, the project investigates the extent to which such discourse data can inform the political process and what impact this has on citizens’ perceptions of politics.