Perola, E. & Todorovic, S. (2020). Exploratory visual methods to aggregate origin-destination geodata. In Muukkonen, P. (Ed.): Examples and progress in geodata science , pp. 53–65. Department of Geosciences and Geography C19. Helsinki: University of Helsinki. Chapter VI Exploratory visual methods to aggregate origin-destination geodata Perola, E., Todorovic, S., Muukkonen, P. & Järv, O.*
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[email protected] , University of Helsinki
[email protected] , University of Helsinki
[email protected] , University of Helsinki *Corresponding author
[email protected] Abstract This study used exploratory visual methods to aggregate Twitter mobility data in the Helsinki Metropolitan Area into postal code areas. Further, this study attempted to visualize the realistic movements of people in a custom-made network between the postal code areas. Twitter mobility data provided by the Digital Geography Lab at the University of Helsinki was used as the sample data. Study methods were also exploratory, comparing between two basic methods: custom networks and aggregation to polygons. Results were both visualizations of Twitter data and its users’ movements in a postal code area level, and a base code for further development to fully visualize movement in the Helsinki Metropolitan Area. Keywords: Movement data; Social media data; Visualization Introduction Movements and mobility patterns have recently gained a lot of attention in research (Andrienko & Andrienko, 2013). The emergence of big data suppliers, and particularly geotagged social media data has provided numerous possibilities to explore not only the places people visit, but also the frequency of their movements (Huang et al. 2015; Chua et al.