This project involves reframing social movements as coevolving systems of protest, politics, and news coverage. Papers and models are in process.
Papers on Coevolution Models
- Pamela E. Oliver & Daniel J. Myers. “The Coevolution of Social Movements” Mobilization 8: 1-25. 2003.
Abstract: Movements develop in coevolution with regimes and other actors in their environments. Movement trajectories evolve through stochastic processes and are constrained but not determined by structures. Coevolution provides a theoretical structure for organizing existing understandings of social movements and sharpening future research. Stochastic thinking is essential for recognizing the both the volatility and path dependence of collective action and its underlying structural constraints. Formal models of diffusion, adaptive learning, mutual reinforcement, and inter-actor competition are developed and compared with empirical protest series. Responses to exogenous reinforcement, mutual adaptation in which failure is as important as success, and inter-actor competition are the most plausible mechanisms to account for empirical patterns. Trajectories of action depend upon the number of discrete random actors. Overall, the analysis suggests that movement dynamics are shaped more by interactions with other actors than by processes internal to a movement, and that empirical analysis must be sensitive to the level of aggregation of the data.
- “Networks, Diffusion, and Cycles of Collective Action.” (Pamela E. Oliver and Daniel J. Myers). Social Movement Analysis: The Network Perspective edited by Mario Diani and Doug McAdam. Oxford University Press. 2003.
Abstract: This paper shows how different “network” arguments about how protest spreads imply quite different underlying mechanisms that in turn produce different diffusion processes. There is considerable ambiguity abiout the relationships among networks, diffusion, and action cycles and the way these can be identified in empirical data. We thus both seek to unpack the “network” concept into different kinds of processes, and then show how these different network processes affect the diffusion processes we are studying. We sketch out some formal models to capture some of these dimensions.
- Stella (simulation program) models used in developing the network paper
- Daniel J. Myers and Pamela E. Oliver. “The Opposing Forces Diffusion Model: The Initiation and Repression of Collective Violence.” Dynamics of Asymmetric Conflict 1 (2, July): 164-189. 2008.
- Pamela E. Oliver and Daniel J. Myers. “Formal Models in Studying Collective Action and Social Movements” Methods of Research in Social Movements, Bert Klandermans and Suzanne Staggenborg, editors. University of Minnesota Press. 2002.
Abstract: This chapter gives examples of formal models and simulation in studying collective action and provides some principles guiding good work. Steps: 1) acquire knowledge about the process you want to model; clearly specify the kind of problem you wish to solve; wlect the basic modeling strategy; start simply and build carefully; face the problem of metric; explicitly identify scope conditions and assumptions; analyze the model; assess the fit of the model to criterion data; write about your model.
- An older literature review which sets up this project: Pamela Oliver. “Formal Models of Collective Action.” Annual Review of Sociology Vol. 19. (1993), pp. 271-300.
Abstract: Examines four types of models of collective action (CA): (1) single-actor models that treat the group behavior as given; (2) models of the interdependent aggregation of individual choices into CA; (3) models of the collective decisions of individuals with different interests; & (4) models of the dynamic interactions among collective actors & their opponents. All models require simplifying assumptions about some aspects of a situation so that others may be addressed. The benefits & drawbacks of each model are discussed, & greater attention is urged to technical issues of formal symbolic mathematical analysis, experimental design, response surface analysis, & technical problems in the reduction & presentation of CA.
- An older theoretical paper on these issues: Pamela Oliver. “Bringing the Crowd Back In: The Nonorganizational Elements of Social Movements.” Research in Social Movements, Confict and Change 11: 1-30. 1989.
Abstract: Social movements are exceedingly complex phenomena encompassing the actions of organizations & their members as well as the actions of nonmembers in activities that organizations have nothing to do with, & many even oppose. Crowds & diffuse collectivities are important parts of social movements. An understanding of social movements is sketched here that integrates their organizational & nonorganizational elements & the relations among them, & views them as large, complex sets of collective events oriented toward a general social change goal. Actions can affect the likelihood of other actions by creating occasions for action, altering beliefs, or adding knowledge. The effects of one nation on another are filtered through communication networks & the mass media. Giving attention to how actions affect other actions permits greater understanding of the dynamic processes involved in the growth of widespread social movements.
- Simulations: Links and Software