Measuring Segregation in Bronx
Integrated Social Media Data and Urban Spatial Network
Course: MIT 11.S951 Senseable City: Data and Analytics
Instructor: Cate Heine
Individual Work
Date: Apr.-May, 2022
Segregation has a significant impact on urban development, especially in terms of social equity. Various factors related
to people’s social activity and urban spatial structure could contribute to the segregation index in an urban area. This
research deploys social segregation analysis and urban spatial network assessment by integrating spatial-social
data, to quantify segregation in Bronx. Both home location and visit pattern based segregation are calculated by
leveraging Twitter API. And two sample set with higher and lower entropy is selected for further analysis.
​
The scenario planning could be approached by manipulating live-work symmetry input to eliminate segregation. It turns out that higher entropy mobility mode with intensified, mixed-use development would achieve better social-spatial equity.
KEYWORDS:
Social segregation; social media data; urban network analysis; scenario planning; mix-use development; social-spatial equity
OBJECTIVES
-An understanding of the spatial scale of urban analysis and data
-An ability to interpret big data through technical approaches
-An ability to critically evaluate the results and findings of data analysis
-Knowledge of artificial intelligence applied to urban sciences
-A critical approach to mobility and urban design to avoid segregation
Presentation
Report
