Uncover the nature of overlapping community in cities

Urban spaces, though often perceived as discrete communities, are shared by various functional and social groups. Our study introduces a graph-based physics-aware deep learning framework, illuminating the intricate overlapping nature inherent in urban communities. Through analysis of individual mobile phone positioning data at Twin Cities metro area (TCMA) in Minnesota, USA, our findings reveal that 95.7 % of urban functional complexity stems from the overlapping structure of communities during weekdays. Significantly, our research not only quantifies these overlaps but also …

analysis cities communities community cs.lg data deep learning deep learning framework framework functional graph graph-based minnesota mobile nature phone physics physics.soc-ph social spaces study through twin urban usa