Abstract
The purpose of this study is to analyze the spatial patterns of location-based social network (LBSN) data in Seoul using the spatial analysis techniques of geographic information system (GIS). The study explores the applications of LBSN data by analyzing the association between Seoul’s Foursquare venues data created based on user participation and the city’s characteristics. The data regarding Foursquare venues were compiled with a program we created based on Foursquare’s Python API. The compiled information was converted into GIS data, which in turn was depicted as a heat map. Cluster analysis was then performed based on hotspots and the correlation with census variables was analyzed for each administrative unit using geographically weighted regression (GWR). Based on analytical results, we were able to identify venue clusters around city centers, as well as differences in hotspots for various venue categories and correlations with census variables.
Highlights
With the increasing number of smartphone users, various smartphone apps have been introduced, most popular among which are social network service (SNS) applications such as Twitter and Facebook
In terms of venue categories, the Food (C4) category, which provides information on restaurants, showed the highest percentage at 41.7%, followed by Professional & Other Places (C7) for offices and other facilities at 18.2% and Shop & Service (C9) for clothing stores and other shops at 17.5%. These three categories accounted for about 78% of all venues, indicating that they represent major service facilities in Seoul metropolitan area that draw the highest levels of interest from users
The spatial statistics analysis was performed based on the hotspot analysis of the distribution characteristics for each category
Summary
With the increasing number of smartphone users, various smartphone apps have been introduced, most popular among which are social network service (SNS) applications such as Twitter and Facebook. Social network services that use global positioning system (GPS) location data are referred to as location-based social networks (LBSN), and widely used services include Foursquare and Facebook Places [1] [2]. In Foursquare, social networking takes place around venues, and various studies have been conducted on venue characteristics using statistical analysis [3] [4]. A typical approach is to create a heat map using the geographic information system (GIS) and venues’ coordinates to analyze their spatial distribution properties within a city. (2015) Spatial Analysis of Location-Based Social Networks in Seoul, Korea. Journal of Geographic Information System, 7, 259-265.
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