09-05, 15:15–15:45 (UTC), Track 1 (Mitxelena)
Detect migration flows worldwide using geolocated Twitter data: routes, settlement areas, mobility to more than one country, spatial integration in cities, etc.
Traditionally, migration and refugee flows information is obtained from surveys and border control operatives. Here we propose a method to detect migration flows worldwide using geolocated Twitter data. In particular and as a practical example, we focus on the current migratory crisis in Venezuela. We study if the flows calculated are quantitatively reliable when compared with official numbers at the country level. Our method is versatile and can be used to study different features of migration such as the routes, settlement areas, mobility to more than one country, spatial integration in cities, etc.
Tracking migration flows worldwide using geolocated Twitter data: routes, settlement areas, mobility to more than one country, spatial integration in cities, etc.
Python Skill Level –basic
Domain Expertise –none
Domains –Big Data, Statistics
Mathematician by formation, she spent most of her life developing software. She started collaborating with the creation of an open source game engine and framework in Tragnarion Studios. Later on, she moved to GridSystems and got involved in the development of an open source grid middleware. Some years later, she started working at IFISC (CSIC-UIB), a research institute. First, she was working on a grid project, but she got interested in data mining and now she is a data specialist working on human mobility and social sciences.