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The Dynamics of Mass Protests (DMP): The Influence of Composition, Demands, and Tactics on Violent Outcomes

Subject Area Political Science
Term since 2022
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 514894404
 
In recent years, the world has experienced an unprecedented number of mass protests. Yet despite numerous valuable research endeavours, one area that has not been systematically addressed is the conditions under which such protest events turn violent. This is a significant limitation, as violent protests have serious detrimental effects: They may harm people as well as infrastructure (e.g., Santiago de Chile 2019–20), erode trust between citizens and government (e.g., Gezi Park, Turkey 2013), and polarize societies (e.g., Charlottesville, USA 2017). To address this shortcoming, the Dynamics of Mass Protest (DMP) project’s main objective is to answer the following research question: Why do some protests turn violent while others do not? We propose a systematic study of the heterogeneous and dynamic nature of protests by focusing on within-protest features related to protest composition, demands, and tactics. The DMP project will use a multidisciplinary methodology. It will collect and analyse original within-protest data using advanced computer vision tools and complement this with qualitative case studies. The DMP project has three key objectives. First, research innovation and impact. The DMP will collect and analyse a comprehensive, disaggregated dataset on within-protest features and outcomes across cases. Results will be published in peer-reviewed journals and presented at workshops and international conferences. Second, the DMP project is strongly committed to disseminating empirical findings to academics, decision makers, and the public through policy workshops, public forums, and policy briefs. Finally, the project aims to translate scientific ethical values into the expanding research area of computer vision and its interdisciplinary links with the social sciences. We will develop a standardized protocol to guarantee that information extracted from images is professionally handled.
DFG Programme Research Grants
 
 

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