Conflicts are a driving force of social change and a supporting element of modern democracies. This is especially true for regulated conflicts such as party competition. By continuously balancing opposing interests, conflicts of this kind make a significant contribution to social integration. However, as soon as conflicts unfold in an unregulated manner – the spectrum ranges from hate speech online to collective violence offline – they can undermine the social order.
Against this background, this interdisciplinary project examines the changing structures and dynamics of social conflicts in Germany. Applying NLP methods, digital data sources (news portals and platforms such as Twitter) as well as the protest-relevant reporting of selected print media are processed to develop a comprehensive database. The data is analysed using qualitative and quantitative methods (discourse analysis, protest event analysis as well as machine learning methods). For further insights into the structural development of protest movements and conflicts, network methodologies are employed.
The project’s central research questions are:
- How have social conflict structures in Germany changed over the past 20 years?
- What are the consequences for democracy given the increasing shift of conflicts to social media?
- What are the conditions for transforming unregulated conflicts into regulated ones?