(And in-progress projects)
Predictive Analytics Engine
Jetson is a predictive analytics platform aimed at providing better data to deliver better decisions. We measure multiple variables to see how changes may effect internally displaced populations. Jetson is an experimental project launched by UNHCR’s Innovation Service in 2017 to better understand how data can be used to predict movements of people in Sub-Saharan Africa, particularly in the Horn of Africa.
The Predictive Analytics Engine (Jetson) is an applied predictive analytics project taking concrete steps to provide insights on the future of displacement.
The project is the first step in understanding data about a) the population flow and b) some of the most common variables that are correlated with the population flow. The project focused on the catalysts that might cause people to flee their homes in the Somalia situation. The main objective is to make predictions about potential displacement events by utilizing data mining, statistics, modeling, machine learning, and artificial intelligence to analyse different data and yield some preliminary conclusions.
Video: Insights from the project’s UX Designer on the challenges and the importance of predictive analytics in the humanitarian sector.
The Innovation Service with the support of UN Global Pulse commenced a big data sentiment analysis with the Regional Bureau for Europe during the Europe Refugee Crisis with the aim of providing decision makers with additional context to the situation as it unfolded within Europe. Part of the exercise was simply to work out how big data – in this case, social media data – could be used to ameliorate UNHCR’s understanding of a complex, and unique situation. The experiment continues to unfold, taking a range of shorter and longer term events into account.
The monitor was set up within Foresight tool of Crimson Hexagon platform for understanding collective opinion, feelings, statements and their changes over time, identifying patterns of sentiment derived from them particularly of publicly available information the Twitter social media platform. The purpose of this research is to better understand host community sentiment in light of global events so UNHCR can have more timely decision-making driven by big data analysis.