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

Abstract only.

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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.