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Open AccessArticle

Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network’s Data from Weibo

by Naimat Ullah Khan 1,2,3,*, Wanggen Wan 1,2 and Shui Yu 3
1
School of Communication & Information Engineering, Shanghai University, Shanghai 200444, China
2
Institute of Smart City, Shanghai University, Shanghai 200444, China
3
School of Computer Science, University of Technology Sydney, NSW 2007, Australia
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(2), 70; https://doi.org/10.3390/ijgi9020070
Received: 15 December 2019 / Revised: 10 January 2020 / Accepted: 19 January 2020 / Published: 21 January 2020
(This article belongs to the Special Issue Smart Tourism: A GIS-Based Approach)
The aim of this study is to analyze and compare the patterns of behavior of tourists and residents from Location-Based Social Network (LBSN) data in Shanghai, China using various spatiotemporal analysis techniques at different venue categories. The paper presents the applications of location-based social network’s data by exploring the patterns in check-ins over a period of six months. We acquired the geo-location information from one of the most famous Chinese microblogs called Sina-Weibo (Weibo). The extracted data is translated into the Geographical Information Systems (GIS) format, and compared with the help of temporal statistical analysis and kernel density estimation. The venue classification is done by using information regarding the nature of physical locations. The findings reveal that the spatial activities of tourists are more concentrated as compared to those of residents, particularly in downtown, while the residents also visited suburban areas and the temporal activities of tourists varied significantly while the residents’ activities showed relatively stable behavior. These results can be applied in destination management, urban planning, and smart city development. View Full-Text
Keywords: LBSN; KDE; Weibo; tourism; GIS LBSN; KDE; Weibo; tourism; GIS
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Khan, N.U.; Wan, W.; Yu, S. Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network’s Data from Weibo. ISPRS Int. J. Geo-Inf. 2020, 9, 70.

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