Abstract
This paper analyzes the imbalance of interprovincial population flow during the Spring Festival travel rush in China, using big data obtained through Baidu Migration, in terms of population flow during the festival and the normalized unbalanced coefficients of edge and node method for analysis, from which the following findings emerge: (1). The imbalance in population flow network during the Spring Festival travel rush is significant, with unbalanced coefficients and relevant frequencies of the population flow network in the Eastern and Western Regions being significantly higher than in other regions. The unbalanced coefficients in the Central Region are lower, followed by corresponding frequencies, while the unbalanced coefficients in the Northeast Region are evenly distributed with the lowest frequencies. The population flow toward the West and Northwest are relatively concentrated, while the population flow toward the South and Southwest are relatively scattered. (2). The regional imbalance during the Spring Festival travel rush has characteristics of spatial agglomeration, where a strongly-connected Southeast Subsystem and a weakly-connected Western Subsystem are formed; there is a significant leverage effect in Guangdong Province, which greatly affects the regional imbalance. Three characteristics emerge in the distribution of regional population flow—the outflow, inflow, and outflow along the Eastern, Central and Western strips/lines, respectively. The paper emphasizes the importance of researching imbalance issues, clarifies the difference between the imbalance of the population flow network and the imbalance involved in previous population research fields, and discusses the Spring Festival Effect in terms of population flow and deficiencies in research.
Highlights
Based on big data on population flow during the Spring Festival travel rush obtained from Baidu Migration, this paper proposes a normalized unbalanced coefficient-based analysis of edge and node to examine the imbalance of population flow between provinces in China, and draws the following conclusions: First, the population flow network during the Spring Festival travel rush in China presents a high level of imbalance in general
Whether measured by the imbalance coefficient of edge or node, the population flow network during the Spring Festival travel rush shows a significant level of imbalance
Spatial agglomeration is mainly reflected in the close connection between the highly-unbalanced outflow area and its surrounding areas, which results in the formation of a local subsystem; leverage effect is mainly reflected in the fact that some strong nodes of population flow in the network are highly-unbalanced, and these few strong nodes play a dominant role in the network, being the main force causing the imbalance; zonality is mainly reflected in the gradient change of the imbalance in the east–west direction
Summary
“The major contradiction of our society has been transformed into a contradiction between the growing needs of the people for a better life, and the unbalanced and inadequate development,” which is one of the most typical features of new urbanization [1, 2] and pointed out by Xi Jinping, the president of the People’s Republic of China in the report of the 19th National. There has been abundant research in this aspect, for example, Liang et al [12] explored the spatial mobility of interprovincial population flow based on the tables of China’s population census and the micro data samples of population census [12]; Duan [13] adopted the measurement model of population flow and economic growth to measure the regional disparity of population distribution in three regions: China as a whole, and the Eastern and the Western regions of China separately [13]; Liu et al [15] identified the balanced active region of population flow and other types of regions by using the composite index of net migration rate and total migration rate [14]; Cao et al [15] used the data of long tables obtained from the 5th and the 6th Population Census to explore population migration changes [15]; Li [18] explored population distribution from the multicenter and dispersion dimensions and identified the spatial structure of different types of cities [16]. Compared with the static perspective of traditional spatial distribution, the imbalance of population flow network focuses on the node itself (traditional cities and regions), and focuses on the interaction between nodes and the process of population flow. The scope of application of normalized unbalanced coefficient as a method to measure the imbalance is not just limited to the national scale, but can be extended to the regional and global scale, as well as to the analysis of traffic network, social network, knowledge network, and other fields
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