Using protest event data to visually reconstruct episodes of contention: Representation, heuristic, and analysis

Mans Lundstedt - University of Gothenborg
Using protest event data to visually reconstruct episodes of contention: Representation, heuristic, and analysis

Abstract
This presentation suggests visual reconstruction as a method for applying protest event analysis in the study of contentious episodes. By illustrating events as points on a temporal grid – alongside other types of events and moments of inactivity – this method makes it possible to bridge qualitative case studies with the conventional quantitative approach to protest event analysis in small- and medium-N designs. It reduces the data in ways that allow for systematic analysis and comparison, while maintaining the attention to case-specific dynamics otherwise reserved for narrative methods. Applying the method on cases of protest campaigns against migrant accommodation in Sweden, I discuss its representational, heuristic, and analytical usages. As a mode of representation, the method allows researchers to illustrate time and temporal dynamics in ways that are not attainable through conventional modes of statistical representation, while minimizing the amount of noise arising from qualitative narratives. As a heuristic device, the method allows researchers to scan and compare the shape of multiple narratives at once, promoting hypothesis construction and the development of formal causal mechanisms. The grid format can be exploited to apply formal analytical methods, including the calculation of the intensity of protest campaigns at different points in time, the speed of reactions to potential triggering events, and the decay of mobilizing effects. The method also opens for the use of qualitative comparative analysis. The presentation ends with a discussion of the method’s limitations, including problems of geographical and temporal scalability, its reliance on a linear conception of time, and its potentially limited usefulness for comparison across studies.