The relationship between urban human dynamics and land use types has always been an important issue in the study of urban problems in China. This paper used location data from Sina Location Microblog (commonly known as Weibo) users to study the human dynamics of the spatial-temporal characteristics of gender differences in Beijing's Olympic Village in June 2014. We applied mathematical statistics and Local Moran's I to analyze the spatial-temporal distribution of Sina Microblog users in 100 m × 100 m grids and land use patterns. The female users outnumbered male users, and the sex ratio (SR varied under different land use types at different times. Female users outnumbered male users regarding residential land and public green land, but male users outnumbered female users regarding workplace, especially on weekends, as the SR on weekends (SR was 120.5) was greater than that on weekdays (SR was 118.8). After a Local Moran's I analysis, we found that High-High grids are primarily distributed across education and scientific research land and residential land; these grids and their surrounding grids have more female users than male users. Low-Low grids are mainly distributed across sports centers and workplaces on weekdays; these grids and their surrounding grids have fewer female users than male users. The average number of users on Saturday was the highest value and, on weekends, the number of female and male users both increased in commercial land, but male users were more active than female users (SR was 110).
Moreover, regarding mobility patterns and practices in terms of time and space in Shanghai, Lei et al. REF used location data from Weibo to study the human dynamics of the spatial-temporal characteristics of gender differences and check-in behavior in Beijing's Olympic Village and stated that female users outnumbered male users in social media activity.
Spatial-Temporal Analysis of Human Dynamics on Urban Land Use Patterns Using Social Media Data by Gender
ISPRS Int. J. Geo-Information
ISPRS Int. J. Geo-Information
Geography Computer Science