论文标题
通过网络分析和潜在空间表示调查内部迁移：土耳其的应用
Investigating internal migration with network analysis and latent space representations: An application to Turkey
论文作者
论文摘要
人类的移民模式会影响地理上人口特征的重新分布，并且由于这种分布与社会和经济成果密切相关，因此研究内部移民的结构和动态在理解和设计此类系统的政策中起着至关重要的作用。我们对2008年至2020年土耳其内部迁移的结构和动态进行了深入的研究。我们确定了一组经典的迁移定律，并通过各种方法进行检查，以进行签名网络分析，自我网络分析，表示网络学习，时间稳定性分析，社区检测和网络可视化。研究结果表明，与经典的迁移法相一致，大多数迁移联系在地理上是界限的，涉及几个涉及具有较大经济活动的城市的例外，主要的迁移流与相反方向的迁移流相反，存在明确定义的迁移途径，并且在调查期间通常稳定迁移系统。除了这些一般结果外，我们还为土耳其提供了独特而具体的见解。总体而言，我们在文献中首次采用的新型工具集允许从复杂的网络的角度研究选定的迁移定律，并阐明了对不同地理的未来移民研究。
Human migration patterns influence the redistribution of population characteristics over the geography and since such distributions are closely related to social and economic outcomes, investigating the structure and dynamics of internal migration plays a crucial role in understanding and designing policies for such systems. We provide an in-depth investigation into the structure and dynamics of the internal migration in Turkey from 2008 to 2020. We identify a set of classical migration laws and examine them via various methods for signed network analysis, ego network analysis, representation learning, temporal stability analysis, community detection, and network visualization. The findings show that, in line with the classical migration laws, most migration links are geographically bounded with several exceptions involving cities with large economic activity, major migration flows are countered with migration flows in the opposite direction, there are well-defined migration routes, and the migration system is generally stable over the investigated period. Apart from these general results, we also provide unique and specific insights into Turkey. Overall, the novel toolset we employ for the first time in the literature allows the investigation of selected migration laws from a complex networks perspective and sheds light on future migration research on different geographies.
