Manifold Cities: Social variables of urban areas in the UK

TL;DR

This paper applies diffusion maps, a manifold learning technique, to UK census data to uncover underlying social structures, revealing key variables like student density and poverty as primary factors in urban social variation.

Contribution

It introduces the use of diffusion maps to analyze complex census data, identifying key social variables influencing urban areas in the UK.

Findings

University student density and poverty are major explanatory variables.

Diffusion maps reveal hidden social structures in census data.

Analysis focuses on Bristol and surrounding areas.

Abstract

In the 21st century ongoing rapid urbanization highlights the need to gain deeper insights into the social structure of cities. While work on this challenge can profit from abundant data sources, the complexity of this data itself proves to be a challenge. In this paper we use diffusion maps, a manifold learning method, to discover hidden manifolds in the UK 2011 census data set. The census key statistics and quick statistics report 1450 different statistical features for each census output area. Here we focus primarily on the city of Bristol and the surrounding countryside, comprising 3490 of these output areas. Our analysis finds the main variables that span the census responses, highlighting that university student density and poverty are the most important explanatory variables of variation in census responses.