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ISPRS Int. J. Geo-Inf. 2016, 5(11), 210; doi:10.3390/ijgi5110210

Analysis of Attraction Features of Tourism Destinations in a Mega-City Based on Check-in Data Mining—A Case Study of Shenzhen, China

1
College of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
2
Shenzhen Key Laboratory for Optimizing Design of Built Environment, Shenzhen 518060, China
3
Shenzhen Key Laboratory of Spatial Smart and Services, Shenzhen 518060, China
*
Author to whom correspondence should be addressed.
Academic Editors: Yichun Xie, Xinyue Ye and Wolfgang Kainz
Received: 21 September 2016 / Revised: 4 November 2016 / Accepted: 7 November 2016 / Published: 10 November 2016
(This article belongs to the Special Issue Spatiotemporal Computing for Sustainable Ecosystem)
View Full-Text   |   Download PDF [4614 KB, uploaded 10 November 2016]   |  

Abstract

Location-based service information, provided by social networks, provides new data sources and perspectives to research tourism activities, especially in highly populated mega-cities. Based on three years (2012–2014) of approximately 340,000 check-in records collected from Sina micro-blog at 86 tourist attractions in Shenzhen, a first-tier city in southern China, we conducted a comprehensive study of the attraction features involving different aspects, such as tourist source, duration of stay, check-in activity index, and attraction correlation degree. The results showed that (1) theme parks established in the early 1990s were the most popular tourist attractions in Shenzhen, but a negative trend was detected in the check-in population; (2) compared with check-in times from surrounding activities and the kernel density of tourists, most destinations in Shenzhen showed a lack of attraction, failing to make the most of their geographic accessibility; and (3) the homogeneity and inconvenient traffic conditions of major tourist destinations leading to the construction of a tourism tour chain has become a challenge. The results of this study demonstrate the potential of big-data mining and provide valuable insights into tourism market design and management in mega-cities. View Full-Text
Keywords: check-in data; tourist destination; tourist scenic spot; attraction feature check-in data; tourist destination; tourist scenic spot; attraction feature
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Gu, Z.; Zhang, Y.; Chen, Y.; Chang, X. Analysis of Attraction Features of Tourism Destinations in a Mega-City Based on Check-in Data Mining—A Case Study of Shenzhen, China. ISPRS Int. J. Geo-Inf. 2016, 5, 210.

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