Abstract <p>The pervasive use of social media has surpassed traditional temporal and spatial boundaries, fundamentally reshaping how user-generated content is produced, disseminated, and consumed. Posts from bloggers and other content creators typically contain multi-dimensional information, including semantic content and geographic tags. However, existing studies often analyze textual data or trajectory data in isolation, overlooking the correlations between these dimensions. To bridge this gap, we propose a novel visualization approach that captures the spatio-temporal-semantic coupling embedded in users’ social media data. Our method integrates a honeycomb layout for constructing semantic maps with customized visual encodings, enabling the simultaneous exploration of individual trajectory patterns and semantic attributes. We develop an interactive visualization system based on a dataset of Xiaohongshu blogger posts, supporting multi-scale analysis from macro-level trends to micro-level details. Case studies demonstrate the system’s effectiveness in revealing bloggers’ content creation patterns and behavioral characteristics.</p> Graphical abstract <p></p>