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Making Governments More Transparent: Using Big Data and Experiments to Change Government Behavior


Term:

IAP

Department:

17: Political Sciences

Faculty Supervisor:

F. Daniel Hidalgo

Faculty email:

dhidalgo@mit.edu

Apply by:

01/15/2019

Contact:

dhidalgo@mit.edu

Project Description

How transparent are local governments in the US? WHat kinds of pressures are most likely to induce local governments to improve their level of transparency? To answer these questions, I have developed a methodology using machine learning to measure the degree of government transparency in local government websites in the US. This data has revealed wide variation in the degree to which local governments make it easy to observe their internal operations through budgets, meeting minutes, etc. To understand the best way to reduce these disparities in transparency, I am engaging in a set of randomized trials where this information is given to either the governments themselves or to local media organizations. Students in this UROP will help me improve the machine learning methodology and conduct the experiments. This will involve collecting and checking data, contacting governments and local media sites, and conducting background research.

Pre-requisites

Some prior experience working with data is beneficial, but not absolutely necessary.