Topological Influence and Locality in Swap Schelling Games

Residential segregation is a wide-spread phenomenon that can be observed in almost every major city. In these urban areas residents with different racial or socioeconomic background tend to form homogeneous clusters. Schelling’s famous agent-based model for residential segregation explains how such clusters can form even if all agents are tolerant, i.e., if they agree to live in mixed neighborhoods. For segregation to occur, all it needs is a slight bias towards agents preferring similar neighbors. Very recently, Schelling’s model has been investigated from a game-theoretic point of view with selfish agents that strategically select their residential location. In these games, agents can improve on their current location by performing a location swap with another agent who is willing to swap. We significantly deepen these investigations by studying the influence of the underlying topology modeling the residential area on the existence of equilibria, the Price of Anarchy and on the dynamic properties of the resulting strategic multi-agent system. Moreover, as a new conceptual contribution, we also consider the influence of locality, i.e., if the location swaps are restricted to swaps of neighboring agents. We give improved almost tight bounds on the Price of Anarchy for arbitrary underlying graphs and we present (almost) tight bounds for regular graphs, paths and cycles. Moreover, we give almost tight bounds for grids, which are commonly used in empirical studies. For grids we also show that locality has a severe impact on the game dynamics

A social network perspective on the interaction between policy bubbles

Studies of policy bubbles have so far ignored the possibility that a policy bubble in a given policy domain or jurisdiction may constitute an information event for another policy bubble that has been inflated elsewhere. In addition, studies of policy diffusion have paid little attention to the transmission of imperfect and wrongful policy valuations through social networks. To bridge these gaps, this article develops a theoretical framework and methodological toolbox for explaining the potential impact of interbubble dynamics on the sustainment of policy bubbles. This is achieved by focusing on: (i) the diffusion of interbubble connectivity information through social networks characterized by varying levels of segregation; (ii) the perceptions of distorted or corrected information by individuals at the receiving end as being factual, thus requiring no gap-filling by policy actors, or as an opinion that therefore requires gap-filling; (iii) the derived consequence in terms of simple or complex contagion; and (iv) its impact on the sustainment of policy bubbles. The main contribution of the article lies in unpacking the potential causal mechanisms through which a policy bubble can be sustained, even if positive feedback processes and contagion in the jurisdiction within which it developed no longer bolster its support bases