Addressing Temporal Dynamics in Collective Action Processes: Sustained Co-Participation and Turning Point in Brokerage

A central question in the current academic debate is how to use social network analysis to empirically address the temporal dimension of collective action (CA) phenomena. Process-oriented strands of literature suggests the role of events to be regarded as fundamental in order to address this issue from a theoretical perspective. Indeed, over the years, the study of events has acquired considerable relevance in the fields of CA and social movements research. Introducing the protest event analysis method, the political process tradition has shed light on the temporal dimension of these phenomena by including events as the main unit of analysis. Often, however, it underestimated – or omitted altogether – the relational dimension underlying these, preferring an explanation based on an aggregative perspective. Furthermore, the exclusive focus on overt actions, such as protests, in manifest phases of mobilisation has resulted in an omission of all those social situations of which CA processes are composed of and are organised around, especially in the latency phases that are argued to characterise them. The multimodal network analytical approach has proven fruitful in addressing these gaps by focusing on the duality of events and actors over time. Events are understood to be contexts for tie transformation; social settings in which ties among actors are formed, maintained or dissolved. At the same time, events can also be regarded as non-agentic entities, and their relational investigation reveals the unfolding of the collective action processes’ structure and related turning points. However, the methods employed in previous empirical research have not facilitated a systematic approach to the issue of network variation over time. The orderability of events that punctuates the development of action trajectories, as well as the volatility of CA actors, have rarely been considered. The aim of this contribution is to present new advances in the application and expansion of the bi-dynamic linear graph model (BDLGM) to address this gap. In particular, this model allows for the incorporation of the temporal dimension into the analysis by means of simultaneous tracing of both single actors’ trajectories and trajectories of co-participation among them. Drawing upon the potential opportunities presented by this new structural configuration of relations among actors, as delineated by the model, we hereby propose two theoretically grounded measures: sustained co-participation and turning point in brokerage. Leveraging the advantages deriving from the structural layout resulting from the application of the BDLGM, the first aims to introduce a score designed to analyse the sequentiality of events in order to assess the impact of co-participation over time in a collective action process. The second, building on the concept of turning point as an event during which a brokerage mechanism activates, applies distance measures in order to identify the joint role of events and their participants in shaping the overall relational structure configuration. This contribution is an elaboration of our ongoing doctoral research projects, which focus respectively on the digital rights field in Europe and the mobilisation of Fridays for Future in Italy.