Data Science in Political Science

Date that the article being summarized was published: January 10, 2022

Article Overview

Data scientists have begun applying machine learning and other data science concepts to political science issues. One issue they have begun to work on is state redistricting based on population sizes. Computing power and statistics can quickly create district borders that equally represent districts. Another issue data scientists have taken to is understanding the causal factors of political unrest in the US and abroad. Different groups have been working on these issues across the world using similar computing tools.

Prescribing Political Boundaries

In Minnessota, a group of data scientists had been iterating through “millions of maps” after identifying one as fit to be examined by a judicial commission that selects which district boundaries will be used for voting in future elections. In this instance, the computers run through many different options, but they rely on people to set priorities for what each district should look like.

Understanding Unrest Amongst Citizens

Another area of interest for data scientists in the political science field is in tracking political unrest. A group called CoupCast is using methods such as gradient boosting and deep neural nets to analyze variables that could predict the likelihood of a political coup. Similar kinds of work has happened overseas through a company named OmniSci. OmniSci looked at social media posts in attempt to track the Arab Spring in 2011.

Author Information

The author of this article titled “Data Science Finds New Uses in Political Science” was written and edited by Alex Woodie. Alex is the managing editor of Datanami, a subsection of Tabor Communications. He is also a senior editor at IT Jungle.

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Discussion

As a student in an undergraduate public policy program, this article makes me curious about why data science is not discussed as frequently in my public policy classes. I feel that computing power could certainly be leveraged to evaluate problems such as how to make tax forms more efficient and how much of the national budget should be invested in space technology. I hope to blend these disciplines together in my own work as the groups that were discussed did in shaping district borders and understanding political movements.

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