9 Data Analytics and Displacement: Using Big Data to Forecast Mass Movements of People

In recent years, the global population of people forcibly displaced by conflict and persecution has reached levels unprecedented since World War II. Acute natural hazards also lead to large-scale movement of people, some temporarily and others permanently. Since 2008, the number of disaster-displaced averaged 21.5 million each year (IDMC, 2016). In many cases, both human-made and natural factors precipitate large-scale displacement, as witnessed by recurrent famines in Somalia caused by the confluence of drought, conflict, and political instability that impede access to food relief. This chapter identifies novel big data sources, methodologies, and challenges that need to be addressed in order to develop more robust, timely, and reliable evidence-based systems for detecting and forecasting forced migration in the context of humanitarian crises.