Introduction to Events & Networks Symposium

Abstract

Prompted by developments in dynamic network analysis, historical network research, and decision theory, Marissa King, Balázs Kovács, and I organized a one-day workshop in the fall of 2016 around the theme of “Networks and Events” at the Yale Institute for Network Science (YINS), cosponsored by YINS and the Initiative on Leadership and Organization at the Yale School of Management. We were able to host only a fraction of the exciting scholars whose work bears on the interrelation of these two topics; nevertheless, the workshop was a generative event. One product was the collection of papers that forms the substance of the following symposium. The following four papers are similar in that they address the relationship between events and networks by conceptualizing and analyzing how events can be linked into patterned configurations that can predict and explain social outcomes and behavior. All depict episodes that are eventful in the colloquial sense of being remarkable and deviating from the mundane and routine. The set of empirical phenomena this captures is quite broad, and the papers describe a wide range of phenomena, including interactions between many people at once, killings, insurgencies, and moments of historical importance. Conceptual differences are also evident. Events are treated variously as social actors (represented by nodes), the ties that link social actors into networks, and networks themselves. The papers, however, are consistent in challenging—but also extending—existing theoretical approaches to events and eventfulness. William Sewell defined events as brief but significant moments that produce large-scale and lasting structural transformations. If structural transformation is defined as changes in the patterns of relationships that hold together the social body, each of the papers suggests that events cannot be moments that produce structural change because the structures of relations that matter are both cross-sectional and longitudinal. These structures are the complex, dynamic patterns of relational transformation and change that occur over time. Thus, for example, the simultaneity or sequential nature of interactions can have an independent effect on information or market exchange, and the order in which counterinsurgency forces secure areas and cultivate widespread public support can determine the outcomes of conflicts. The problems of dynamic network analysis have increasingly forced network researchers to confront the problem that structure is not static and that the way it interacts with time is not limited to persistence or transformation. This issue has taken on even greater