Methods: Machine Learning,Reproducible & Open Science
Fields: Political Science, Public Policy, Social Science

Project Leader: Professor José Manuel Magallanes

Associate Researchers: Tyler McCormick, Ernesto Calvo, Mason Porter, James Fowler and Sang Hoon Lee.

Associated Institutions:

  • Grupo Interdisciplinario de Investigación Computacional de la Complejidad Social (GICS) de la Pontificia Universidad Católica  (PUCP)
  • Departamento de Ciencias Sociales y Centro de Investigaciones Sociológicas, Económicas, Políticas y Antropológicas (PUCP)

Collaborators from Peru: José Luis Incio,  Marylia Cruz, Sakimi León and Tania Paredes

Data planned to be collected: Electoral (National Jury of Elections), Higher Education ( Ministry of Education),  Police (Police Census and Ministry of Interior), Native communities (Ministry of Culture), and bill cosponsorship (National Congress). Only publicly available data will be considered.

This project aims at integrating different sources of data to produce prototypes that improve political decision making and serve a as an accessible source of relevant information services for the citizen. Several techniques from Data Science and Computational Social Science will be used along this project to build the prototypes. As a prototype gets requested by a collaborating institution, a process of knowledge transfer will start, so that this public organization starts its way towards Open Data and computational intelligence projects.

JMagallanesImprovingPoliticalDecisionMaking

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