Abstract
<jats:p>Digital platforms, algorithmic recommendation systems, and user-generated content are rapidly influencing urban commercial branding. Commercial spaces like lifestyle streets, shopping districts, cafés, restaurants, and cultural consumption areas are no longer solely promoted through official branding or traditional advertising in the context of platform-based urban consumption; instead, they are constantly reconstructed through posts, short videos, searches, saves, likes, comments, and shares. With a comparative focus on Xiaohongshu and Douyin, this study investigates how algorithmic recommendation processes affect urban commercial brand communication. It looks at three typical urban commercial areas: Beijing Sanlitun, Chengdu Taikoo Li, and Shanghai Anfu Road, using a comparative case study methodology. The results demonstrate that Xiaohongshu tends to support a cumulative and decision-oriented visibility model in which users can plan future consumption with the aid of trust-based suggestions, searchable information, guide-style notes, and saving behavior. On the other hand, brief films, visual rhythm, emotional ambiance, and algorithmic amplification can quickly boost exposure in Douyin's more immediate and attention-oriented visibility model. Additionally, user comments demonstrate how audiences engage in meaning-making through desire to consume, information inquiry, emotional reaction, debates about authenticity, and privacy concerns. Three dimensions are the focus of the analysis: comment content, interaction data, and content form. This study advances our knowledge of urban commercial branding in the context of platformization and offers useful recommendations for companies looking to create distinctive cross-platform communication strategies.</jats:p>