Sparking Events, Emotional Climates, and Cascades of Cultural Identity Conflicts

• Applicants: Dr. Felix Schulte; Dr. Christoph Trinn
• Subject Area: Political Science
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 493809260

Inter-communal and self-determination conflicts revolve around cultural identities that are highly emotionally charged. They often manifest in quickly escalating mass behaviour such as protests and riots. How can we explain such non-linear short-term escalation dynamics?The project addresses three prevailing shortcomings: the focus on time-invariant structural factors, the overemphasis of top-down rationalist or framing approaches and the lack of integration of collective emotions into the research on cultural identity conflicts. To overcome the overreliance on quasi-constant structural factors and elite-driven strategies in existing research, we take a processual, bottom-up perspective and conceptualize conflictive mass behaviour as “cascades”. These are understood as propagations of self-organizing conflictive mass behaviour of varying intensity and extensity spontaneously sparked by triggering events. The concept of triggering event remains undertheorized as the relative importance of time-invariant contexts and time-variant disruptive incidents is contested. To address this shortcoming, we turn to self-organized criticality (SOC), a feature of complex systems where epidemic behaviour arises through the triggering of cascades. The Forest-Fire-Model (FFM), a widely discussed mechanism of SOC, unites time-invariant structural conditions and extremely time-invariant triggering events. The FFM serves as a suitable heuristic to answer the research question.In our model, an emboldening emotional climate provides the “fuel” that is sparked by a triggering event. As a necessary intermediate step, we expect that the activated potential translates into action through collective self-organization within cultural identity groups. By combining triggering events, collective emotions and self-organization, our model provides an innovative and comprehensive explanation of the non-linear short-term escalation dynamics of collective mass behaviour in cultural identity conflicts.The project applies a mixed-methods approach. It starts off with the qualitative identification of triggering events and a measurement of the intensity and extensity of cascades utilizing a novel dataset compiled in preparatory work. In a second step, we subject the model to a quantitative test. For this purpose, we measure collective self-organization and emotional climates by conducting network and sentiment analyses using Twitter data. The latter analyses require the construction of an appropriate dictionary. By including relevant context variables in matching and regression models, we seek to assess the robustness of our model across different structural and institutional settings. The third step consists of a qualitative test of the model. Based on the statistical evaluation, we select typical and deviant cases for process tracing analysis. In cooperation with local case experts, conflict-specific case studies are prepared and subjected to a systematic cross-case comparison.

• DFG Programme: Research Grants