Gothenborg, Sweden : Chalmers University of Technology, 2017. - VI, 422 p.
(Doktorsavhandlingar vid Chalmers tekniska högskola ; 4215)
Zugleich: Gothenburg, Chalmers University of Technology, Dissertation
Abstract: This thesis engages with questions on the boundary between what has traditionally been understood as social and natural. The introductory essay contextualizes the specific contributions of the included papers, by noting and exploring a reinvigoration of 'naturalism' (the notion of a continuity between the human realm and the rest of natural phenomena) under the banner of Complexity Science. This notion is put under explicit light, by revisiting the age-old question of naturalism and connecting ideas in complexity science with the work of e.g. Roy Bhaskar, Mario Bunge, William Wimsatt, and David Lane. A philosophical foundation for a complexity science of societal systems is thereby sketched, taking the form of an integrative and methodologically pluralist 'complex realism'. The first two papers provide a theoretical perspective on the distinction between social and natural: Paper I notes that societal systems combine two qualities that are commonly referred to as complexity and complicatedness into an emergent quality that we refer to as 'wickedness', and that is fundamentally and irreducibly different from either quality in isolation. This explains the recalcitrance of societal systems to the powerful approaches that exist for dealing with both of these qualities in isolation, and implies that they indeed ought to be treated as a distinct class of systems. Paper II uses the plane spanned by complexity and complicatedness to categorize seven different system classes, providing a systematic perspective on the study of societal systems. The suggested approach to societal systems following from these conclusions is exemplified by three studies in different fields and empirical contexts. Paper III combines a number of theories that can be seen as responses to wickedness, in the form of evolutionary developmental theories and theories of societal change, to develop a synthetic theory for cultural evolution. Paper IV exemplifies how simulation can be integrated with social theory for the study of emergent effects in societal systems, contributing a network model to investigate how the structural properties of free social spaces impact the diffusion of collective mobilization. Paper V exemplifies how digital trace data analysis can be integrated with qualitative social science, by using topic modeling as a form of corpus map to aid critical discourse analysis, implying a view of formal methods as aids for qualitative exploration, rather than as part of a reductionist approach.
In: International journal of communication, Vol. not yet known, pp. not yet known
In: Internet histories, 1 (2017) 1/2, p. 160-172
In: The datafied society : studying culture through data / Mirko Tobias Schäfer... (eds.)
Amsterdam : Amsterdam University Press, 2017. - P. 75-94
Armel Jacques Nzekon Nzeko'o
Abstract: We study strategic interaction between agents who distill the complex world around them into simpler situations. Assuming agents share the same cognitive frame, we show how the frame affects equilibrium outcomes. In one-shot and repeated interactions, the frame causes agents to be either better or worse off than if they could perceive the environment in full detail: it creates a fog of cooperation or a fog of conflict. In repeated interaction, the frame is as important as agents' patience in determining the set of equilibria: for a fixed discount factor, when all agents coordinate on what they perceive as the best equilibrium, there remain significant performance differences across dyads with different frames. Finally, we analyze some tensions between incremental versus radical changes in the cognitive frame.
In: Complex networks VIII : proceedings of the 8th Conference on Complex Networks ; CompleNet 2017 / Bruno Goncalves... (eds.)
Cham : Springer, 2017. - P. 81-92
(Springer proceedings in complexity)
Abstract: We explore a new mechanism to explain polarization phenomena in opinion dynamics. The model is based on the idea that agents evaluate alternative views on the basis of the social feedback obtained on expressing them. A high support of the favored and therefore expressed opinion in the social environment, is treated as a positive social feedback which reinforces the value associated to this opinion. In this paper we concentrate on the model with dyadic communication and encounter probabilities defined by an unweighted, time-homogeneous network. The model captures polarization dynamics more plausibly compared to bounded confidence opinion models and avoids extensive opinion flipping usually present in binary opinion dynamics. We perform systematic simulation experiments to understand the role of network connectivity for the emergence of polarization.