A collaborative research article published on Computers, Environment and Urban Systems

A collaborative research regarding "overlapping community detection from mobility networks" has just been published in Computers, Environment and Urban Systems.

Urban spaces have always served as arenas of information exchange—from cafés and teahouses to parks and transit stations. Building on this idea, we reconceptualize population movement as information flow and present the Geographic Interaction Propagation (GIP) model, which weights travel intensity between locations, incorporates distance decay, and applies automated anomaly detection to extract meaningful overlapping community patterns.

🔎 Through a Washington D.C. shared e-scooter case study, GIP uncovers hidden urban community structures and pinpoints information hubs—parks, plazas, and schools—that not only channel mobility but also reflect deeper socioeconomic differences.

Luo, P., Song, C., Li, H., Zhu, D., & Duarte, F. (2025). Modeling shared micromobility as a label propagation process for detecting the overlapping communities. Computers, Environment and Urban Systems. 1-22. https://doi.org/10.1016/j.compenvurbsys.2025.102336