Complex Systems and Data Science for Humanitarian Response
Conference Year
January 2021
Abstract
The use of new technologies and unconventional data has been increasingly used in policy making and humanitarian responses in events of distress.
In this work we present multiple methodologies to work with unstructured data given in the form of mobility and expenditure patterns as well as text based surveys in order to build a better relief allocation program where, when and by whom is most needed in a wide diverse set of contexts such as earthquakes, violence, educational gaps and epidemics.
We also explore a mathematical model of human behavior to explain how collective patterns arise from individual ones in these types of events and how can it be used to forecast and build preventive policies instead of reactive ones.
Primary Faculty Mentor Name
Nicholas Cheney
Faculty/Staff Collaborators
Nicholas Cheney, Sam Fraiberger, Esteban Moro, Lucio Melito, Bernardo Garcia-Bulle, Lorenzo Lucchini, Laurent Hébert-Dufresne
Status
Graduate
Student College
College of Engineering and Mathematical Sciences
Program/Major
Complex Systems
Primary Research Category
Engineering & Physical Sciences
Complex Systems and Data Science for Humanitarian Response
The use of new technologies and unconventional data has been increasingly used in policy making and humanitarian responses in events of distress.
In this work we present multiple methodologies to work with unstructured data given in the form of mobility and expenditure patterns as well as text based surveys in order to build a better relief allocation program where, when and by whom is most needed in a wide diverse set of contexts such as earthquakes, violence, educational gaps and epidemics.
We also explore a mathematical model of human behavior to explain how collective patterns arise from individual ones in these types of events and how can it be used to forecast and build preventive policies instead of reactive ones.