TY - JOUR
T1 - Complex network of United States migration
AU - Charyyev, Batyr
AU - Gunes, Mehmet Hadi
N1 - Publisher Copyright:
© 2019, The Author(s).
PY - 2019/12/1
Y1 - 2019/12/1
N2 - Economists and social scientists have studied the human migration extensively. However, the complex network of human mobility in the United States (US) is not studied in depth. In this paper, we analyze migration network between counties and states in the US between 2000 and 2015 to analyze the overall structure of US migration and yearly changes using temporal analysis. We aggregated network on different time windows and analyzed for both county and state level. Analyzing flow between US counties and states, we focus on the migration during different periods such as economic prosperity of the housing boom and economic hardship of the housing bust. We observed that nodes at county and state level usually remain active, but there are considerable fluctuations on links. This indicates that migration patterns change over the time. However, we could identify a backbone at both county and state levels using disparity filter. Finally, we analyze impact of the political and socioeconomic factors on the migration. Using gravity model, we observe that population, political affiliation, poverty, and unemployment rate have influence on US migration.
AB - Economists and social scientists have studied the human migration extensively. However, the complex network of human mobility in the United States (US) is not studied in depth. In this paper, we analyze migration network between counties and states in the US between 2000 and 2015 to analyze the overall structure of US migration and yearly changes using temporal analysis. We aggregated network on different time windows and analyzed for both county and state level. Analyzing flow between US counties and states, we focus on the migration during different periods such as economic prosperity of the housing boom and economic hardship of the housing bust. We observed that nodes at county and state level usually remain active, but there are considerable fluctuations on links. This indicates that migration patterns change over the time. However, we could identify a backbone at both county and state levels using disparity filter. Finally, we analyze impact of the political and socioeconomic factors on the migration. Using gravity model, we observe that population, political affiliation, poverty, and unemployment rate have influence on US migration.
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U2 - 10.1186/s40649-019-0061-6
DO - 10.1186/s40649-019-0061-6
M3 - Article
AN - SCOPUS:85060656414
VL - 6
JO - Computational Social Networks
JF - Computational Social Networks
IS - 1
M1 - 1
ER -