|
|
|
| STUDY ON SPATIO-TEMPORAL DISTRIBUTION OF RESIDENTS' NOCTURNAL ACTIVITIES OF XI'AN BASED ON MICRO-BLOG |
| CHEN Hong-fei1, LI Jun-yi1, QIN Chao1, LIU Guang2, SUN Jiu-lin1,3 |
1. Tourism and Environment College, ShaanXi Normal University, Xi'an 710062, China;
2. Network Information Center, ShaanXi Normal University, Xi'an 710062, China;
3. Institute of Geographical Science and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China |
|
|
|
|
Abstract In recent years, social media has gained worldwide development. Twitter and Weibo are regarded as lifelogs. Users are able to record personal lives through social media, and meanwhile the locating function of mobile phones helps users to identify their location. Scholars all over the world use social media, for example twitter, as social sensors to carry out studies on social events, public opinion monitoring, traffic accidents testing and natural disaster warnings and forecasts. The article focuses on Sina Weibo, one of the most widely used social media in China, as the data resource to analyze residents' outdoor activities. 1323577 Weibo data were collected dated from July 2th to Dec. 2th in 2013 in Xi'an through Sina API with the technology of Ajax. The data were firstly structured, and then users in Xi'an were solely selected according to their registration location. Data posted from 5pm to 12am were selected and divided into 4 groups with those gathered in every two hours in one group. Lastly, with the application of Getis-OrdGi* in ArcGIS10.1, in the form of statistics, the temporal and spatial distribution characteristics of Xi'an residents' night life activities were demonstrated. According to the findings from popularity chart and increase or decrease chart, residents' night life in Xi'an city is closely associated with their living area, status in a large scale. In terms of time, the number of Weibo in general increases firstly, and then decreases, which indicates Xi'an residents night life are mainly scheduled on the researched period of time, and beside the number of residents in commercial districts has an increase-decrease tendency. Spatially speaking, traditional commercial districts are still preferred by residents, and they are most crowded in the researched period of time.
|
|
Received: 22 April 2014
|
|
|
|
|
|
|
2015, Vol. 30 
