Abstract
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 ( S R 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 S R on weekends ( S R was 120.5) was greater than that on weekdays ( S R 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 ( S R was 110).
Highlights
The relationship between human dynamics in urban areas and land use types has always served as one of the foundations for the study of geography [1]
We applied mathematical statistics and Local Moran’s I to analyze the spatial-temporal distribution characteristics of Sina Location Microblog users according to sex cohorts for land use patterns in urban areas, with the users’ coordinates objectively uploaded by the Global Positioning System (GPS) interfaces of smart phones
We found that the number of overall female users outnumbered male users (SR was 78.5)
Summary
The relationship between human dynamics in urban areas and land use types has always served as one of the foundations for the study of geography [1]. Many researchers have obtained the geographical location information of users from bus smart cards, taxi Global Positioning System (GPS) trajectory data, the GPS interface of smart phones, and internet application data, allowing them to study the behavior of users Among these studies, researchers have focused on analyzing each user’s trajectory and hotspot clustering to identify the main urban functional areas. By collecting the sequence of an individual’s GPS data from smart phones and taking into account a user’s sequential visits to locations, scholars built a personalized location recommendation system using the location collection and presented a life pattern normal form to define individual life patterns [11,12] In addition to these data types, social media data have provided another data source for studying the dynamics of population distribution. Other researchers have applied geo-tagged posts of an urban area from Twitter and cloud computing to mine popular travel routes and trajectory patterns [17,18]
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