Discovering Activity Patterns in the City by Social Media Network Data: a Case Study of Istanbul
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Discovering Activity Patterns in the City by Social Media Network Data: a Case Study of Istanbul Taner Üsküplü 1 & Fatih Terzi 2
& Hüma
Kartal 3
Received: 9 November 2019 / Accepted: 3 February 2020/ # Springer Nature B.V. 2020
Abstract With the rapid developments in internet and communication technologies, activities take within the city create a reflection in virtual environments and these traces make visible the relation ties of the city’s dynamic structure. The data generated by mobile devices that take part in everyday life and become integrated with the user’s activities gives valuable information about users’ behavioural trends in the city. This new type of data, called ‘Big Data’ that consist of huge amounts of information with a fine-grained resolution, also help people to make reasoning about the activity pattern formations within the city, with a bottom-up approach. This approach also paves the way for developing a holistic approach. This study aims to discover and analyse the activity patterns of the parts of historical districts of Istanbul by evaluating the data generated from location-based social networks. Foursquare API database is utilised to collect activity data that consist of location, venue, category, and visitor counts (check-in) features. The data mapped and weighted with the check-in counts and spatial statistics analyses held in GIS to discover hotspot and cluster patterns of the activities within the study area. The main finding of the paper is that the spatial distribution of citizens’ demand for products and services creates patterns of emerging urban areas of activity. Keywords Social media network analysis . Activity patterns . Spatial statistics . GIS .
Istanbul
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s12061-02009336-5) contains supplementary material, which is available to authorized users.
* Fatih Terzi [email protected]
1
Architect, DBArchitects Istanbul, Atabey Sok. No:8 Hasanpaşa, 34722 Kadıköy/Istanbul, Turkey
2
Faculty of Architecture, Department of Urban and Regional Planning, Istanbul Technical University, Taşkışla, 34367 Taksim/Istanbul, Turkey
3
Urban Planner, Istanbul, Turkey
T. Üsküplü et al.
Introduction In recent years, Big Data has emerged as a technology integrate more with daily activities. By the widespread use of GPS embedded devices and smartphones; sensors that collect real-time urban information such as transportation, weather, air quality or automated-internet based systems that collects all the data of transactions, governmental data enables people to monitor the activities real or near real-time in the cities. These datasets that contain valuable information about activities, provide us better understanding and sense of how we interact with one another in the city (Batty 2016). The term ‘Big Data’ corresponds to the creation of large quantities of machinereadable data. The information comes from systems that users interact often in dailyroutines by choice or necessity: social media net
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