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This study investigates the coupling and coordination mechanisms between virtual and physical spatial heat in coastal internet-famous streets under the influence of social media. Taking Dalian’s coastal internet-famous street as a case study, user interaction data (likes, favorites, shares, and comments) from the Xiaohongshu platform were integrated with multi-source spatio-temporal big data, including Baidu Heat Maps, to construct an “online–offline” heat coupling and coordination evaluation framework. The entropy-weight method was employed to quantify online heat, while nonlinear regression analysis and a coupling coordination degree model were applied to examine interaction mechanisms and spatio-temporal differentiation patterns. The results show that online heat demonstrates significant polarization with strong agglomeration in the Donggang area, while offline heat fluctuates periodically, rising during the day, stabilizing at night, and peaking on holidays at up to 3.5 times weekday levels with marginal diminishing effects. Forwarding behavior is confirmed as the core driver of online popularity, highlighting the central role of cross-circle communication. The coupling coordination model identifies states ranging from high-quality coordination during holidays to discoordination in daily under-conversion or overload scenarios. These findings verify the leading role of algorithmic recommendation in redistributing spatial power and demonstrate that the sustainability of coastal check-in destinations depends on balancing short-term traffic surges with long-term spatial quality, providing practical insights for governance and sustainable urban planning.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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