Beyond Frequency: Incorporating Time in the Analysis of Political Party Participation in Protests

Time plays a crucial role in the analysis of the relationship between political parties and social movements, yet it is often overlooked in standard quantitative studies. While much ink has been spilt on the conceptual and empirical analysis of the relationship between parties and protest events, relatively little attention has been given to how, over time (rather than how often), parties participate in collective actions. So far, most studies have relied on large datasets of protest events drawn from the daily press, employing quantitative methods such as logistic regression to uncover the frequency of party involvement in social protests. Although these methods have their advantages, they focus on averages and often overlook specific, individual cases and their temporal order. In my study, drawing on data from national newspapers, I will examine Polish protests in 2022 to show how regression analyses can be enriched by adding a qualitative component in the form of network analysis, which directly incorporates the temporal dimension. I employ bi-dynamic line graphs that integrate time into the analysis of social protests, allowing for a more nuanced understanding of individual protest events within the broader flow of protests throughout 2022. The bi-dynamic line graph is an innovative way to visualize the evolution of actor participation in successive protest events. The key implication of this method is that all time steps corresponding to events are directly considered, and actions, connected through shared actor participation, are represented as a stream—a continuous social process unfolding over time. This approach delves into the relationships between protest events and actors, offering deeper insights into how data can be represented in a dynamic temporal framework, beyond traditional regression models.