Migrant mobility flows characterized with digital data
arXiv:1908.02540 · doi:10.1371/journal.pone.0230264
Abstract
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.
12 pages, 7 figures, 5 tables
References in corpus (15)
- Understanding individual human mobility patterns
- The architecture of complex weighted networks
- Human Mobility: Models and Applications
- Geo-located Twitter as the proxy for global mobility patterns
- From mobile phone data to the spatial structure of cities
- Urban Gravity: a Model for Intercity Telecommunication Flows
- Exploring universal patterns in human home-work commuting from mobile phone data
- Cross-checking different sources of mobility information
- A stochastic model of randomly accelerated walkers for human mobility
- Field theory for recurrent mobility
- Influence of sociodemographic characteristics on human mobility
- Immigrant community integration in world cities
- Human diffusion and city influence
- Tweets on the road
- Twitter as a Source of Global Mobility Patterns for Social Good