Forecasting and organizing migration flows still poses an enormous challenge for the European Union and the actors involved. The EU-funded project ITFLOWS therefore aims to generate new insights into migration flows in order to enable decision makers to take meaningful organizational measures. The project focuses on the phases of reception, distribution and integration. Precise models are supposed to provide deeper insights into future migration processes and create the basis for the EUMigraTool.
Based on data from various information sources and in line with humanitarian and fundamental rights requirements, the ICT-based approach generates valuable information that can be used to meaningfully manage and deploy efforts in the initial admission, distribution and integration process.
The procedure is continuously measured against current requirements of legislators, practitioners, NGOs and civil society organizations. In combination with the detailed investigation of migration causes and patterns, but also the public perception by EU citizens, this forms the basis for tailor-made recommendations for action and best practices for legislators, governments and EU institutions.
The consortium coordinated by the University of Barcelona consists of 14 partners from various disciplines to make sure that the complex matter can be comprehensively researched and managed. IGR/FIZ Karlsruhe with its comprehensive expertise in data protection issues, represents a decisive building block in the legally compliant development of the new, data-driven approach. ISE/ FIZ Karlsruhe is responsible for compiling a data set of migration-related messages from the social media platform twitter based on Google trends from the respective home and target countries. The generated data is then analyzed on distributed platforms using deep learning technologies to detect hate speech and extremist opinions.
Project leaders: Prof. Dr. Franziska Boehm, Prof. Dr. Harald Sack
Staff: Thilo Gottschalk, Mehwish Alam
Project term: September 01, 2020 – August 31, 2023