A Study of Users' Movements Based on Check-In Data in Location-Based Social Networks

Abstract

With the development of GPS technology and the increasing popularity of mobile device, Location-based Social Networks (LBSN) has become a platform that promote the understanding of user behavior, which offers unique conditions for the study of users' movement patterns. Characteristics of users' movements can be expressed by places they’ve visited. This paper presents a method to analyze characteristics of users' movements in spatial and temporal domain based on data collected from a Chinese LBSN Sina Weibo. This paper analyzes spatial characteristics of users' movement by clustering geographic areas through their check-in popularity. Meanwhile, temporal characteristics and variation of users' movements on the timeline is analyzed by applying statistical method.

Jinzhou Cao(曹劲舟)

Assistant Professor

My research interests Urban big data mining, Geo-AI and Urban Analytics.