NeighViz: Towards Better Understanding of Neighborhood Effects on Social Groups with Spatial Data

TL;DR

NeighViz is a visual analytics system designed to help social scientists explore and understand how neighborhood environments influence behaviors across different social groups using detailed spatial data.

Contribution

The paper introduces a novel analytical framework and an interactive system, NeighVi, for examining multivariate neighborhood effects on social behaviors, addressing limitations of traditional methods.

Findings

Effective exploration of neighborhood effects demonstrated in case study

System usability confirmed through social science expert feedback

Enhanced understanding of local environment impacts on behaviors

Abstract

Understanding how local environments influence individual behaviors, such as voting patterns or suicidal tendencies, is crucial in social science to reveal and reduce spatial disparities and promote social well-being. With the increasing availability of large-scale individual-level census data, new analytical opportunities arise for social scientists to explore human behaviors (e.g., political engagement) among social groups at a fine-grained level. However, traditional statistical methods mostly focus on global, aggregated spatial correlations, which are limited to understanding and comparing the impact of local environments (e.g., neighborhoods) on human behaviors among social groups. In this study, we introduce a new analytical framework for analyzing multi-variate neighborhood effects between social groups. We then propose NeighVi, an interactive visual analytics system that helps social scientists explore, understand, and verify the influence of neighborhood effects on human behaviors. Finally, we use a case study to illustrate the effectiveness and usability of our system.