Article ID Journal Published Year Pages File Type
6458374 Applied Geography 2017 12 Pages PDF
Abstract

•Studying urbanization from the perspective of interactions among cities.•Disclosing the spatial differentiation of urbanization using migrant data.•Discovering the groups of cities with a community detection algorithm.•Identifying the importance of cities with the PageRank algorithm.

Because cities have different attractions for laborers, people migrate from city to city, which may widen the gap between cities. Analyzing the fluxes and directions of migrant flows can help us clarify the regional difference of urban development. Using migration data inferred from passenger travels during 2016 Spring Festival from Tencent Location Big Data, this paper analyzed the unbalanced migration between cities and the spatial difference of urban development. Network analysis methods are employed to evaluate interactions among cities. A community detection method identifies 19 city communities, and the directions of migrant flows in the communities are explored. The PageRank algorithm is employed to evaluate the importance of cities on the migration network and divide the cities into 5 grades, and then the hierarchical structure of the migrant network is illustrated and analyzed. Indices based on migrant populations indicate that the most attractive cities for laborers are along the east coast and that cities in the central region export a significant number of laborers. PageRank and attractiveness values are compare with socio-economic data, and the results indicate that both PageRank and attractiveness are positively correlated with the economic and development level of cities, while PageRank works better. It suggests that Spring Festival travel data in China can be used as migration data, however, it should be facilitated with network methods to disclose the relationship between Spring Festival travel and urban development.

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