University of Virginia, Charlottesville, Virginia, United States of America.
University of Florida, Gainesville, Florida, United States of America.
PLoS One. 2021 Jan 27;16(1):e0245712. doi: 10.1371/journal.pone.0245712. eCollection 2021.
What drives the formation and evolution of the global refugee flow network over time? Refugee flows in particular are widely explained as the result of pursuits for physical security, with recent research adding geopolitical considerations for why states accept refugees. We refine these arguments and classify them into explanations of people following existing migration networks and networks of inter-state amity and animosity. We also observe that structural network interdependencies may bias models of migration flows generally and refugee flows specifically. To account for these dependencies, we use a dyadic hypothesis testing method-Multiple Regression- Quadratic Assignment Procedure (MR-QAP). We estimate MR-QAP models for each year during the 1991-2016 time period. K-means clustering analysis with visualization supported by multi-dimensional scaling allows us to identify categories of variables and years. We find support for the categorization of drivers of refugee flows into migration networks and inter-state amity and animosity. This includes key nuance that, while contiguity has maintained a positive influence on refugee flows, the magnitude of that influence has declined over time. Strategic rivalry also has a positive influence on refugee flows via dyad-level correlations and its effect on the structure of the global refugee flow network. In addition, we find clear support for the global refugee flow network shifting after the Arab Spring in 2011, and drivers of refugee flows shifting after 2012. Our findings contribute to the study of refugee flows, international migration, alliance and rivalry relationships, and the application of social network analysis to international relations.
是什么推动了全球难民流动网络的形成和演变?难民流动通常被广泛解释为对人身安全的追求,最近的研究还增加了各国接受难民的地缘政治考虑。我们对这些论点进行了细化,并将其分为人们追随现有移民网络和国家间友好与敌意网络的解释。我们还观察到,结构网络的相互依存关系可能会对移民流动模式,特别是难民流动模式产生偏见。为了说明这些依赖性,我们使用了对偶假设检验方法——多元回归-二次分配程序(MR-QAP)。我们对 1991 年至 2016 年期间的每一年进行 MR-QAP 模型估计。多维尺度支持的聚类分析和可视化使我们能够识别变量和年份的类别。我们发现支持将难民流动的驱动因素分为移民网络、国家间友好与敌意这两个类别。这包括一个关键的细微差别,即虽然毗邻关系对难民流动一直保持着积极的影响,但这种影响的程度随着时间的推移而下降。战略竞争也通过对偶级相关性对难民流动产生积极影响,并对全球难民流动网络的结构产生影响。此外,我们发现,自 2011 年阿拉伯之春以来,全球难民流动网络发生了明显变化,难民流动的驱动因素也发生了变化。我们的研究结果为难民流动、国际移民、联盟和竞争关系的研究以及社会网络分析在国际关系中的应用做出了贡献。