In the information age, digital platforms, such as social media and local lifestyle service platforms, have deeply integrated into urban life, subtly shaping spatial regeneration and playing an important role in the process of gentrification, a form of socio-spatial “upgrading” process. This paper takes the central urban area of Nanjing, China as a case study, integrates diverse digital platform data, and employs a Random Forest machine learning model together with SHAP analysis to examine how “physical–virtual” factors jointly contribute to the process of gentrification. The findings reveal that the structure of neighborhoods remains a strong explanatory factor for gentrification (38.64%), while variables related to digital platforms account for a cumulative explanatory power of 46.09%, and the number of neighborhood service facilities contributes the least (15.26%). Digital platforms convert UGC into digital capital that shapes investment and regeneration, while reinforcing segregation through algorithmic visibility. To address these challenges, urban renewal and governance policies should prioritize zoning protections and rent control measures, enhance platform transparency and fair visibility, and simultaneously promote digital literacy programs.
He et al. (Mon,) studied this question.