DATA MINING THE CITY

tutor: Danil Nagy / partners: Tin Yan Cheung, Xiaobei Yang, Huiwen Zhu/ tool: Python, QGIS, Excel, Illustrator, Grasshopper(Migration Animation), Tilemill(online interactive map)

URBAN RESEARCH AND DATA VISUALIZATION PROJECT

As both physical and economical relations between Hong Kong and Shenzhen are getting closer since 1997, increased mainlanders travelling in Hong Kong. Tourism industry in Hong Kong metropolitan area has extraordinary social and economic impact on city future development. The tourism industry as a whole contributed 3.9% to the economy in 2012. Tourists contribute to the local economy and employment which trigger city’s investment in conservation, infrastructure and promotion for growing of tourists and local people. However, due to the rapid change of tourists’ preferences and expectation, it’s hard to predict tourists’ movement by traditional method of interview and census. Our project aims to create a new methodology that can forecast the trend of attractions in the city and the future tourism market. To research tourism industry’s unprecedented growth and tourist travel pattern, we try to use Weibo, one of China’s most popular social media, which has over 500 million registered users at the end of 2012. There are 156.5 million monthly active users and 69.7 million daily active users by the end of June 30, 2014.  This giant pool of data on Weibo’s open API platform is available to everybody today. There are over 20,000 check-in points in Hong Kong and Shenzhen. Our project hypothesized that SZers travelling in HK would be attracted by the top ranking hotspots as listed in Tripadvisor, and by tracing the moving patterns of SZers who check-in weibo in those hotspots, we would be able to find where else SZers go beyond those hotspots. By figuring those“Hidden Hotspot.

TripAdvisorHotSpot

DensityAndCheckingNumber

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