Arbeitsbereich

Migration und Mobilität

Auf einen Blick Projekte Publikationen Team

Projekt

Patterns of Migration and Mobility in Response to International Conflicts and Wars

Asli Ebru Sanlitürk, Athina Anastasiadou, Carolina Coimbra Vieira, Emilio Zagheni; in Zusammenarbeit mit Vytenis Deimantas (Netherlands Interdisciplinary Demographic Institute, The Hague, Niederlande), Francesco C. Billari (Bocconi University, Milan, Italien), Artem Volgin (The University of Manchester, Großbritannien), Douglas Leasure (University of Oxford, Großbritannien)

Ausführliche Beschreibung

International conflicts and wars often trigger mass as well as unexpected migration flows. It becomes imperative in times of crises to understand the scale, patterns, and characteristics of refugees, both for the purposes of humanitarian assistance and policy response. However, timely information on the people fleeing from conflicts and wars is typically lacking due to the difficulty of conducting field work promptly and because of ethical considerations. People moving in response to international conflicts and wars are considered to be among the hardest-to-reach populations.

We address the need for timely data to gain deeper insights into the patterns of people fleeing from international conflicts and wars and to shed light on these people's characteristics. We primarily use novel approaches and timely data to estimate the scale and patterns of conflict- and war-induced mass migration events. A secondary aim is to provide insights into the characteristics and needs of the refugees, focusing mostly on the migration process and the early phases of post-migration.

In studies on forced migration, the data available are often collected at the aggregate level only, and this is often done at post-migration, i.e., after arrival in the host country. With conflict- and war-induced migration, the events that force people to move unravel rather rapidly; the preparation for migration thus is short, and the intention and means to move are hard to observe. The relevant decision-making processes take place before and during the move, and large-scale data are lacking at these stages. In the context of conflict- and war induced migration, data may be available at the aggregate level, but this depends on the host country. Data that would provide insights into the characteristics of refugees, however, are  harder to obtain. This may be due to a lack of connection and trust as to the members of the target refugee population, high costs of field work, and ethical issues. The lack of data hinders us to gain a better understanding of refugee characteristics and needs. We fill some of these information gaps, using case studies and novel data approaches.  

The project in the main (i) introduces novel digital trace data as a predictor of mass forced migration patterns, (ii) contributes to studies on forced migration and humanitarian responses by providing methods for gathering information on the characteristics and needs of migrating populations, and (iii) informs policy decision-making by providing evidence-based research findings on migration at times of international conflict and wars.

We currently have studies in progress; these use webscraping, online search data from Google Trends and Yandex Keyword Statistics, and Wikipedia data. The analyses are built on the following case studies: the Mediterranean refugee crisis in the wake of the Syrian Civil War, the Ukrainian refugees following the Russian invasion of the Ukraine, and the exodus of Russian nationals as a reaction to the aforementioned war.  

One of these studies tested the potential of online search data as a predictor to observe the moves of Syrian refugees within Turkey, the host country. It measured interest in a province through Google Trends scores for the name of the given province and exploited the alphabetical differences between the languages of the host and refugee populations. The study has revealed that online search data can help predict the movements of refugee populations within the host country and that the provisional estimates are confirmed by register data about six weeks later.

Publikationen

Anastasiadou, A.; Volgin, A.; Leasure, D. R.:

War and mobility: using Yandex web searches to characterize intentions to leave Russia after its invasion of Ukraine

Demographic Research 50:8, 205–220. (2024)