Abstract
While segregation is usually evaluated at the residential level, the recent influx of large streams of data describing urbanites’ movement across the city allows to generate detailed descriptions of spatio-temporal segregation patterns across the activity space of individuals. For instance, segregation across the activity space is usually thought to be lower compared with residential segregation given the importance of social complementarity, among other factors, shaping the economies of cities. However, these new dynamic approaches to segregation convey important methodological challenges. This paper proposes a methodological framework to investigate segregation during working hours. Our approach combines three well-known mathematical tools: community detection algorithms, segregation metrics and random walk analysis. Using Santiago (Chile) as our model system, we build a detailed home–work commuting network from a large dataset of mobile phone pings and spatially partition the city into several communities. We then evaluate the probability that two persons at their work location will come from the same community. Finally, a randomization analysis of commuting distances and angles corroborates the strong segregation description for Santiago provided by the sociological literature. While our findings highlights the benefit of developing new approaches to understand dynamic processes in the urban environment, unveiling counterintuitive patterns such as segregation at our workplace also shows a specific example in which the exposure dimension of segregation is successfully studied using the growingly available streams of highly detailed anonymized mobile phone registries.
Highlights
The historical and unprecedented growth of income inequality worldwide has pushed segregation to a pivotal concept in the description of social systems [1]
We show the benefit of developing new approaches to understand dynamic processes of social segregation
We show how the exposure dimension of segregation can be successfully studied from the increasingly available cellphone registries by combining network analysis with segregation indexes
Summary
The historical and unprecedented growth of income inequality worldwide has pushed segregation to a pivotal concept in the description of social systems [1]. Standard methods have mostly relied on static views seeking to describe and characterize residential ghettoization [10,11] and several indices have been put forward to quantify inequality across residential areas [12], the most paradigmatic example being the Duncan dissimilarity index [13], which measures the percentage of minority population that would have to be relocated in order to perfectly integrate among the distribution of residents of a region [14] These indices do not often consider social interactions in other contexts such as work and leisure to define segregation. Farber et al [14] used the timegeography framework and origin–destination surveys to estimate the social interaction potential index, given by the spatio-temporal prism generated between all possible paths between home and work
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