Tourist-resident divergence in multimodal social sensing and its implications for urban regeneration

Urban perception is fundamental to understanding the built environment and has been increasingly observed through social sensing, yet most studies overlook differences between population groups. This limitation becomes especially consequential in urban regeneration contexts, where tourists and residents often experience and represent space differently. This study proposes a group-sensitive multimodal framework to compare how tourists and residents express urban environments across text, image, and emotion. Using 14,300 geo-tagged posts and 78,632 images from Beijing, we quantify narrative divergence and analyze its relationship with built-environment (BE) factors. Results show a clear modality difference: visual divergence remains low (Mean JSD image = 0.140), textual narratives differ greatly (Mean JSD text = 0.435), and emotional divergence is moderate (Mean ED = 0.146). These differences are associated with BE factors including functional mix, spatial visibility, and amenity context. In urban regeneration contexts, these divergences help identify tensions and offer insights for planning strategies and design decisions. More broadly, the study reveals that conventional aggregated social sensing may produce a filter effect by amplifying dominant narratives while neglecting everyday experiences of different user groups. It highlights the need for differentiated user perspectives in multimodal social sensing to support more inclusive urban analysis and planning.