Abstract
The volume, velocity, and variety of data that are now becoming available allow us to study urban environments based on human behaviour with a spatial, temporal, and thematic granularity that was not achievable until now. Such data-driven approaches open up additional, complementary perspectives on how urban systems function, especially if they are based on user-generated content (UGC). While the data sources, such as social media, introduce specific biases, they also open up new possibilities for scientists and the broader public. For instance, they provide answers to questions that previously could only be addressed by complex simulations or extensive human-participant surveys. Unfortunately, many of the required data sets are locked in data silos that are accessible only via restricted APIs. Even if these data could be fully accessed, their naïve processing and visualization would surpass the abilities of modern computer architectures. Finally, the established place schemata used to study urban spaces differ substantially from UGC-based point-of-interest (POI) schemata. In this work, we present a multi-granular, data-driven, and theory-informed approach that addresses the key issues outlined above by introducing a theoretical and technical framework to interactively explore the pulse of a city based on social media.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Cartographica: The International Journal for Geographic Information and Geovisualization
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.