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Title RETRACTED: Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network's Data from Weibo (Retracted article. See vol. 9, 2020)
ID_Doc 44586
Authors Khan, NU; Wan, WG; Yu, S
Title RETRACTED: Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network's Data from Weibo (Retracted article. See vol. 9, 2020)
Year 2020
Published Isprs International Journal Of Geo-Information, 9, 2
DOI 10.3390/ijgi9020070
Abstract 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.
Author Keywords LBSN; KDE; Weibo; tourism; GIS
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
EID WOS:000522449700010
WoS Category Computer Science, Information Systems; Geography, Physical; Remote Sensing
Research Area Computer Science; Physical Geography; Remote Sensing
PDF https://www.mdpi.com/2220-9964/9/2/70/pdf?version=1606980115
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