Motivations

Social inequalities and segregation remain significant challenges in contemporary cities, influencing access to resources, opportunities, and social interactions. Indeed, urban environments act as spatial sorting mechanisms, where an individual's location plays a crucial role in determining their access to the city's resources and influences their potential for social mobility.  This spatial inequality contributes significantly to the broader rise in social inequalities, as access to urban amenities and opportunities varies markedly across different neighborhoods and regions within cities.

Additionally, digital inequality has emerged as a critical factor in urban mobility, with differing levels of engagement with digital technologies influencing access to transportation services. This disparity affects not only mobility but also broader social participation, highlighting the need to understand how digital engagement shapes access to resources and services and vice versa.

The spatial dimension of inequality could be explored through the integration of mobility data, which reveals how daily activities, often extending beyond residential spaces, contribute to varying levels of socio-spatial segregation.

At the same time, social networks amplify these inequalities. Mechanisms such as homophily and triadic closure deepen social segregation, leading to fragmented network structures that mirror the spatial divides in urban areas so that, similarly to what happens in urban spaces, marginalization in a social network can restrict opportunities and limit access to crucial resources, such as information, social support, and social mobility.

Recent work emphasizes the importance of comprehending digital inequality in the context of urban development. Policymakers, practitioners, and academics must collectively address these issues, as the implications of digital exclusion continue to deepen.

The rise of smart city technologies has been met with both optimism and scepticism, particularly regarding their potential to exacerbate income inequalities. Factors such as unequal diffusion of information and communication technologies, affordability barriers for low-income residents, disparities in human capital, and the involvement of private sector actors have been identified as contributing to these concerns. 

However, empirical evidence on this matter remains sparse. In fact, recent studies suggest that, when well-implemented, smart cities are associated with lower levels of income inequality.

All things considered, digital technologies, including mobile internet usage, location-based services, social media platforms, and online information environments, offer new ways to explore these inequalities and segregation helping us to understand how people move through urban space, engage with others, and access services. 

These digital traces are valuable tools for understanding patterns of exclusion and disparities in access to essential urban resources (such as housing, healthcare, education, and transportation), and for assessing how social networks can help observe these dynamics or, conversely, how they may reinforce and exacerbate these inequalities.

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