Exploring the potentials and possible uses of Location Based Social Network Data for urban and transportation planning in Turku City Centre.
Social media has become a common feature of our everyday life. For researchers, social media provides large amounts of readily accessible, on-time and qualitatively rich data that can be used to study urban activities and people’s interactions. The specific characteristics of different forms of social media, such as Twitter, Instagram and Foursquare, open different avenues for both quantitative and qualitative analysis.
A vast majority of data collected by social networks and crowd-sourced platforms is made available to the public by the users themselves, sometimes more and other times less consciously. This data can be collected and analysed by third- parties, providing a granular and detailed description of social processes through space and time.
In our research, we are particularly interested in the analytic use of Location Based Social Network data (from here onwards called LBSNd) combined with other data sources used in urban and traffic planning, in this case remote mapping and configurational analysis. This hybrid approach can offer interesting insight into the daily and weekly rhythms of use of space as well as the meanings people attach to particular urban spaces. In such analysis LBSNd works as an invisible treasure of data and meta-data produced directly by the urban population, including visitors. In this explorative study on Turku we will present just a few possible uses of this data.
Our main research interest is to study how Location Based Social Network data (LBSNd) can be used for the urban and transportation planning. In case of City of Turku, this was done to discuss the current spatio-temporal dynamics in its city centre, indicating potentials for further development, and assessing how a new tram line that may be constructed would change the situation.
Overall, the tasks were focused on exploring which streets and spaces in Turku’s city centre are more likely to attract people today and how the situation might change if a new tram line will be constructed. The study was assigned by the City of Turku and funded from Turku Urban Research Programme.
Activity patterns are studied by mapping all the uses that are likely to attract certain kind of human activities at the ground level. In addition, the study focuses on the interaction between different uses during specified periods of time.
A dataset with all possible sources is created to describe and assess accessibility in Turku to study where people are most likely to pass by. Perceived and spatial accessibility is analysed using Space Syntax analysis, and car traffic and light traffic data provided by the City of Turku is included together with the OpenStreetMap users’ GPS traces and Turku’s public transportation network.
