Data mining and visualization research of check-in data

Abstract

Crowd sourcing geographic data, which is contributed by lots of non-professionals and provided to the public, is an open source geographic data with characteristics of large data volume, high currency, abundance information and low cost. As a kind of crowd sourcing geographic data, check-in data contains multitudes of social attribute data and becomes a research hotspot of international geographic information science in the recent years. Take check-in data of Jiepang for instance, this paper studies spatiotemporal visualization method of check-in data, proposes a hotspot detection method based on frequency and variation thematic map of check-in data, and does some research on the spatiotemporal mining method of check-in data in the end. The correlation analysis experiment between the resident population and the amount of check-in user in different district shows that the check-in data has a high correlation with urban economy and population, indirectly reflects the distribution situation of urban economy and population, can be used for the analysis of national socioeconomic situation.