Monitoring migration flows is crucial to respond to humanitarian crisis and to design efficient policies. This information usually comes from surveys and border controls, but timely accessibility and methodological concerns reduce its usefulness. Here, we propose a method to detect migration flows worldwide using geolocated Twitter data. We focus on the migration crisis in Venezuela and show that the calculated flows are consistent with official statistics at country level. Our method is versatile and far-reaching, as it can be used to study different features of migration as preferred routes, settlement areas, mobility through several countries, spatial integration in cities, etc. It provides finer geographical and temporal resolutions, allowing the exploration of issues not contemplated in official records. It is our hope that these new sources of information can complement official ones, helping authorities and humanitarian organizations to better assess when and where to intervene on the ground.
Pulses, waves, and cascades in collective migration dynamics
University of Vienna（维也纳大学）；Complexity Science Hub（复杂性科学中心）；University of Waterloo（滑铁卢大学）；University for Natural Resources and Life Sciences（自然与生命科学大学）
The adoption of non-pharmaceutical interventions and the role of digital infrastructure during the COVID-19 Pandemic in Colombia, Ecuador, and El Salvador
One country, multiple portraits: representativeness in GPS-based mobility data is source-specific and spatially dependent
University of Liverpool（利物浦大学）；El Colegio de Mexico（墨西哥学院）；Central European University（中欧大学）；Center for Research and Advanced Studies of the National Polytechnic Institute, Irapuato Unit（墨西哥国立自治理工学院高级研究中心伊拉普阿托分部）；University College London（伦敦大学学院）
Digital Epidemiology with Awareness-Based Event-Triggered Migration in Networked Cyber-Physical Systems
Southwest University（西南大学）；University of Electronic Science and Technology of China（电子科技大学）；University of Maribor（马里博尔大学）；Community Healthcare Center Dr. Adolf Drolc Maribor（马里博尔市阿道夫·德罗尔克博士社区医疗中心）；Kyung Hee University（庆熙大学）；Korea University（高丽大学）；Potsdam Institute for Climate Impact Research（波茨坦气候影响研究所）；Humboldt University of Berlin（柏林洪堡大学）
Reliability-Aware Refinement of High-Resolution Human Mobility Origin-Destination Tables under Sparsity and Suppression
Institute of Systems and Information Engineering, University of Tsukuba（筑波大学系统信息工程学院）；GEOTRA Co., Ltd.（GEOTRA有限公司）；School of Data Science, Yokohama City University（横滨市立大学数据科学学院）
