Identifying urban spatial structure and urban vibrancy in highly dense cities using georeferenced social media data

Abstract

Tracking human activities with social media (online social networks) and point of interest data to understand human dynamic distribution, behavior, and high-density urban environments is gaining importance in the domain of urban studies. Recently, social media data have proven to be a rich source of information, providing a novel way to derive urban spatial structures and their impact on the quality of life. Yet, integration of this wisdom in urban planning and policymaking has not been comprehensively investigated in high-density cities such as Hong Kong as it relates to spatial configurations. This study aims to investigate spatial structures and analyze social media data to apprise urban planning with knowledge of human activities. This study also seeks to introduce an exploratory analysis to develop a greater understanding of the interaction between social activities and urban space. The results show that function layout defines urban spatial structure and determines human social activities. The research provides insights regarding a better interpretation of the knowledge of social activities, underlying how well social activities reflect the corresponding urban spatial structure and gaining a detailed understanding of their respective variation in activities.