Segregation in urban systems and mobility

Globalization and multiculturalism have both increased the cultural diversity in big cities and magnified the preexisting discrimination and segregation of migrant communities, rooted in multiple social, cultural, historical and economic factors between the origin and destiny countries. In addition to the broad studies of migrant integration and segregation developed by social sciences, the development of spatial segregation metrics is key to understanding the current status of the living conditions of migrants and making sensible choices to face inequality. Within this background, information technologies and social networks provide data on the spatial use of the cities in time and the nationality of their citizens that allow the development of such metrics beyond census and territorial plans.

In this thesis, we use data from Twitter to set up a common reference frame to compare migrant integration among different cities, identify the migrant community of their users via language identification of their tweets and propose a new spatial segregation metric that compares the direct usage of every part of the city between migrant communities and the local one. We use multidimensional scaling to properly visualize how far every user’s visits across the city are from the locals’ visits and give an ordered and structured geometry to their movement across the city. After testing and tuning the different parameters under which to apply the metric with different theoretical cases, we proceed to measure the spatial segregation of every detected migrant community in each of the extracted cities. We perform considering three different time windows: residential, working and leisure hours. This division will allow us to also study segregation in mobility between time windows. The results yield a classification of the cities according to the time window in which the average spatial segregation over their communities is the highest. We analyze the most representative results and relate them to segregation in mobility, the presence of dormitory cities, dispersion and zonification. Finally, we study the best and worst integrated communities of each city for each time window and relate the results to the relationship between Arabic and Latin-American origin countries to North American and European destinies.