Back to News

Si Wu, Journalism Graduate Student, Uses Data to Help Others Understand Political Redistricting

Si Wu. Photo by Matthew Modoono/Northeastern University

Si Wu, a graduate student at Northeastern University’s Master of Arts (MA) in Journalism program, spent the summer as a Data Science Research Fellow at MIT/Tufts University. In this position, Wu conducted research for the Metric Geometry and Gerrymandering Group, a working group led by Moon Duchin of Tufts University and Justin Solomon of MIT that is using math and data to research political redistricting. Wu’s interest in data research, and how it can combine with Journalism, was sparked when she joined Northeastern as a graduate student in 2018. 

When she joined the Northeastern community, Wu had the opportunity to work closely with Aleszu Bajak, who is the graduate program manager in the School of Journalism as well as a freelance science journalist.

“Working with Aleszu transitioned my path from writing to data journalism, which I thought was really interesting,” said Wu.

When she saw the position at Tufts University, she knew it was one that would allow her to embrace this side of journalism that was focused on data, since the group’s mission is to study applications of geometry and computing to U.S. redistricting. When she first started in June,  she had the opportunity to spend two weeks in lectures and six weeks working on group projects. Wu then went on to use programming tools, such as Python, to look at districting plans and some of the key statistics, including population, to try to understand how states are districted. 

She also worked on representing what she found with data visualizations to help her and the group better understand the statistics. The group then used the figures to look at trade-offs when it comes to redistricting. 

During this project, I was exposed to the field of political science and I learned how to use data to address problems in political science and answer questions.

As the Data Science Research Fellow, one of the things Wu was responsible for was designing outreach material for teachers in the area. She created a webpage with Javascript, a programming language used to create interactive data visualizations, displaying information on the history of gerrymandering. She also designed an interactive meta graph for an ensemble of districting plans using D3.js, a JavaScript library for producing dynamic, interactive data visualizations in web browsers.

Her work with Javascript and other tools helped Wu carve out her newest role at Harvard Data Science Review, which she started in September. There, she is a Data Visualization Intern working with programs such as Tableau, Python, and Plotly to effectively design and communicate data science concepts. 

One of the projects she is currently working on is building a template for visualizations that other people can use by just inputting their own data. For that project, Wu is working with R, a free software environment for statistical computing and graphics. 

Her experience at Tufts and Harvard has solidified that data journalism is the field Wu wants to enter after graduation.

I am looking to explore the possibilities in the data viz / data journalism field.

Wu graduated with her undergraduate degree in Physics from Imperial College in London and moved to Boston two years later to start this journey through a graduate degree program at Northeastern. 

“I came to Boston before, and I thought it was a really cool city, so I wanted to apply in schools there,” said Wu.  “I also wanted to do something that was different than my undergrad. I wanted to explore different fields.”

When she learned more about the Journalism program at Northeastern, she knew it would be a great fit. 

“Students are able to do so many different things in this journalism program,” Wu concluded. “You get to explore things with virtual reality, augmented reality, and different ways to tell stories.”

We look forward to hearing more from Si Wu and her adventures in the field!