From Digital Traces to Healthy City Streets: Emotion-Behavior-Environment Links via City Jogging in Beijing

Author Information

Yuanchen Zhao, Tsinghua University, China
Xiaoqing Cheng, Tsinghua University, China

Abstract

Urban streets are expected to support everyday health in high-density cities, yet evidence on what makes them jogging-friendly remains limited. City jogging combines exercise, socializing, and urban exploration, while smartphones and wearable devices record fine-grained runner-street interactions. Using Beijing as a case, this study links emotion, jogging behavior, and street environments to inform healthy street planning. We analyze approximately 67,000 Keep jogging trajectories within Beijing’s Fifth Ring Road and 965 valid public online narratives from Xiaohongshu and Douyin. A contribution-based semantic network analysis, combined with affective cues, identifies four runner profiles: routine fitness, urban exploration, social running, and performance training. K-means clustering summarizes route forms, and street-level jogging intensity is modeled with built-environment and streetscape indicators using random forest regression and SHAP interpretation. The results show that emotion-related jogging produces distinct spatial preferences. Restorative runs are concentrated in parks and neighborhood loops, exploration-oriented runs gravitate to historic districts and landmark corridors, and training runs favor continuous routes such as ring roads. The environmental model further indicates that runnability is shaped by landmark attraction, service nodes, blue-green proximity, route structure, and visual openness. Building on these findings, the study proposes differentiated healthy street strategies, including neighborhood health loops, cultural exploration corridors, continuous training corridors, women- and novice-friendly access, and digital health feedback for adaptive street renewal.

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