Journal
CITIES
Volume 97, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.cities.2019.102523
Keywords
Big data; Human activity; Land use
Categories
Funding
- National Natural Science Foundation of China [41971194]
- Research Center for the Industrial Development of Guangdong and its Regional Cooperation with Hong Kong, Macau and Taiwan
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The application of location-based social media big data in urban contexts offers new and alternative strategies for understanding city liveliness in developing countries where traditional census data are poor. This paper demonstrates how the spatial-temporal distribution of China's Tencent social media usage intensities can be effectively used as a proxy for modelling the geographic patterns of human activity at fine scales. Our results suggest that the spatially-temporally contextualized nature of human activity is dependent upon land use mixing characteristics. With billions of social media data being collected in the virtual world, findings of this study suggest that land use policies to delineating the density, orderly or disorderly geographic patterns of human activity are important for city liveliness.
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