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Investigating internal migration with network analysis and latent space representations: an application to Turkey
1Dept. of Management Information Systems, Boğaziçi University, Bebek, 34342 Istanbul, Turkey.
Social Network Analysis and Mining
|October 17, 2022
Summary
Internal migration in Turkey from 2008-2020 shows geographically bounded patterns, with exceptions for economically active cities. Migration flows are often bidirectional and stable, revealing defined routes and aiding policy design.
Area of Science:
- Social Sciences
- Network Science
- Demography
Background:
- Human migration significantly impacts population distribution and is linked to socioeconomic outcomes.
- Understanding internal migration dynamics is vital for effective policy development.
Purpose of the Study:
- To investigate the structure and dynamics of internal migration in Turkey between 2008 and 2020.
- To apply complex network analysis methods to examine classical migration laws.
Main Methods:
- Utilized signed network analysis, ego network analysis, representation learning, temporal stability analysis, community detection, and network visualization.
- Examined migration data from 2008 to 2020.
Main Results:
- Migration links are predominantly geographically constrained, with notable exceptions for major economic centers.
- Significant migration flows exhibit counter-flows, indicating established routes.
- The Turkish migration system demonstrated general stability over the study period.
Conclusions:
- The study validates classical migration laws within the Turkish context using novel network analysis tools.
- Findings offer unique insights into Turkey's internal migration patterns.
- The employed methodology provides a new perspective for migration research globally.
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