Exploring the effects of urban network topologies on entropy trajectories of segregation

Segregation is a threat to the aspirations of producing a cohesive society and modelling its dynamics can be done in order to help design preventative measures. This work explores the question of whether the network topologies of urban spaces can affect the pace at which populations can become segregated. The simulation dynamics employed augment the canonical Schelling model in such a way that it also captures the affinity for agents to prefer denser regions which also offer sufficient local homogeneity. It is shown that different networks synthetically generated and from real city maps can alter the rate of segregation. The results also show that using the entropy trace on the distribution of agent edge degree across all agents correlates with the segregation reinforcing the relevance of physics inspired modeling of social systems. This investigation shows that it is possible to explore and select network arrangements which can be less conducive towards segregation movements during the stages of urban planning so that the rate is reduced. An additional finding is that the entropic measure is closely associated with the common statistic for such modeling efforts.