AN APPLICATION-ORIENTED IMPLEMENTATION OF HEXAGONAL ON-THE-FLY BINNING METRICS FOR CITY-SCALE GEOREFERENCED SOCIAL MEDIA DATA

Abstract

Abstract. The use of georeferenced social media data (GSMD) for informing municipal policy-making has significant potential, particularly in addressing pressing socio-environmental challenges. Geospatial dashboards have emerged as a powerful tool for knowledge communication and supporting urban sustainability. However, there has been little emphasis on how to display and make GSMD more accessible, partly due to their complex nature. Existing visualization tools lack sophisticated methods, especially for complex urban contexts, and the methodological choice can significantly impact the interpretation of results. In this study, we propose the use of hexagonal binning as an interactive visualization method and assess three different on-the-fly binning metrics for mapping GSMD. We expand the use of the signed chi metric for spatial purposes and apply it in a case study in Bonn, Germany. We evaluate the advantages and disadvantages of the proposed metrics as well as visualizations and highlight the challenges of visualizing GSMD particularly in the context of Instagram. Our findings highlight the importance of using appropriate context-dependent visualization methods when analyzing data at the municipal level.