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利用在线数据测量全球移民流动情况。

Measuring global migration flows using online data.

作者信息

Chi Guanghua, Abel Guy J, Johnston Drew, Giraudy Eugenia, Bailey Mike

机构信息

Meta, Menlo Park, CA 94025.

Department of Sociology, Faculty of Social Sciences, University of Hong Kong, Hong Kong Special Administrative Regions, China.

出版信息

Proc Natl Acad Sci U S A. 2025 May 6;122(18):e2409418122. doi: 10.1073/pnas.2409418122. Epub 2025 Apr 29.

Abstract

Existing estimates of human migration are limited in their scope, reliability, and timeliness, prompting the United Nations and the Global Compact on Migration to call for improved data collection. Using privacy protected records from three billion Facebook users, we estimate country-to-country migration flows at monthly granularity for 181 countries, accounting for selection into Facebook usage. Our estimates closely match high-quality measures of migration where available but can be produced nearly worldwide and with less delay than alternative methods. We estimate that 39.1 million people migrated internationally in 2022 (0.63% of the population of the countries in our sample). Migration flows significantly changed during the COVID-19 pandemic, decreasing by 64% before rebounding in 2022 to a pace 24% above the precrisis rate. We also find that migration from Ukraine increased tenfold in the wake of the Russian invasion. To support research and policy interventions, we release these estimates publicly through the Humanitarian Data Exchange.

摘要

现有的人类移民估计在范围、可靠性和及时性方面存在局限,这促使联合国和《移民问题全球契约》呼吁改进数据收集工作。我们利用来自30亿脸书用户的受隐私保护记录,以月度粒度估算了181个国家之间的移民流动情况,并考虑了脸书用户的选择因素。我们的估算结果与现有的高质量移民衡量指标高度匹配,而且几乎可以在全球范围内得出,并且比其他方法的延迟时间更短。我们估计,2022年有3910万人进行了国际移民(占我们样本中各国人口的0.63%)。在新冠疫情期间,移民流动情况发生了显著变化,在2022年反弹之前减少了64%,反弹后的速度比危机前高出24%。我们还发现,自俄罗斯入侵以来,从乌克兰流出的移民增加了十倍。为支持研究和政策干预,我们通过人道主义数据交换平台公开发布了这些估算结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbd1/12067262/e4b9429cb08a/pnas.2409418122fig01.jpg

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