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http://dx.doi.org/10.7319/kogsis.2015.23.1.023

Analyzing Spatial Correlation between Location-Based Social Media Data and Real Estates Price Index through Rasterization  

Park, Woo Jin (Center of Environmental Remediation and Risk Assessment, Seoul National University)
Eo, Seung Won (Department of Civil & Environmental Engineering, Seoul National University)
Yu, Ki Yun (Department of Civil & Environmental Engineering, Seoul National University)
Publication Information
Journal of Korean Society for Geospatial Information Science / v.23, no.1, 2015 , pp. 23-29 More about this Journal
Abstract
In this study, the spatial relevance between the regional housing price data and the spatial distribution of the location-based social media data is explored. The spatial analysis with rasterization was applied to this study, because the both data have a different form to analyze. The geo-tagged Twitter data had been collected for a month and the regional housing price index about sales and lease were used. The spatial range of both data includes Seoul and the some parts of the metropolitan area. 2,000m grid was constructed to consider the different spatial measure between two data, and they were combined into the constructed grids. The Hotspot Analysis was operated using the combined dataset to see the comparison of spatial distribution, and the bivariate spatial correlation coefficients between two data were measured for the quantitative analysis. The result of this study shows that Seocho-gu area is detected as a common hotspot of tweet and housing sales price index data. though the spatial relevance is not detected between tweet and housing lease price index data.
Keywords
Social Media; Geo-tag; Real Estate Price Index; Grid based Analysis; Hot Spot Analysis; Spatial Correlation;
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Times Cited By KSCI : 2  (Citation Analysis)
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