Drawing on 620,458 public posts on Meta’s CrowdTangle API, Melissa E. Tornari, Amir Abdul Reda, Omolola S. Olarinde used natural language processing (NLP), machine learning and predictive inference to understand how gathering migration-related information changed before and during COVID-19, exploring how it has affected migration aspiration-setting.

The pandemic had a widespread impact on international and internal migration systems, triggering unprecedented disruptions to mobility, reversing migration trends, and creating new, often involuntary, forms of immobility. As an external shock to the economic and social systems that shape migration throughout the entire migration cycle—from departure and transit to entry and return—their research provides a useful test for the analysis of information-seeking behaviors of aspiring migrants and people in transit. In doing so, they gathered new evidence on differences in migration aspiration-setting and information-gathering between origin and transit countries and on how changes in the information-gathering of migration logistics can affect aspiration-setting.

In this seminar, Melissa will discuss how, while most users focus on visa procedures and foreign education and employment opportunities, systematic differences emerge in the aspiration-setting of users from Morocco compared with those from Kenya and Nigeria. Her research also identifies key predictors of these differences. In particular, investigating how an exogenous shock can affect information practices, they found that during the COVID-19 pandemic period the share of migration-related content increased, with heightened attention to emigration logistics, visas, and document services.

The nature of the considered discussion forums (whether of more general interest or specifically related to given countries of departure and/or destination) predicts the degree of variability among discussed topics over COVID-19. Discussions on health and care substantially increased in this period, driven by a demand for carergivers and health workers.

Building counterfactual trends in aspirations in the absence of shortages of healthcare workers across selected destinations, she will stress how this demand-driven change affects the composition of aspiring migrants and their destinations of interest.