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Data Science

Leo Carrico ’20

Beginning his studies as a computer science major at Oakton Community College, Leo Carrico `20 decided instead to pursue data science after transferring to Lake Forest College. Aided by his data science professors, Carrico began developing algorithms to observe the persuasive effects of language on human psychology through social media. Involved with that research, Carrico earned a James Rocco Quantitative Data Research Scholarship.

How did you land your data science research opportunity?

Professor Arthur Bousquet and Professor Vivian Ta would eat lunch together and talk about projects they were working on and Professor Ta mentioned she might have a research opportunity that would work out for a computer science student. Professor Bousquet asked me if I was interested and I was, so we went to Professor Ta to talk about her project and how we could help her through data science.

What was your role on the project?

For my research, I went to an online forum where people specifically go to post their opinion and ask commenters to persuade them to change their view. My job was to take the comments that were capable of changing the original poster’s opinion and run data science algorithms on them to figure out which comments were most likely to persuade people to change their opinions. Doing that, I pulled out data like which words have more influence, what kind of words have influence, and how long their sentences must be in order to influence people.

How do you think that having this research experience will help you after graduation?

I’ve been looking at master’s programs in data science and, when I’m talking to recruiters for those programs, they always mention that doing both research in data science and getting a degree in the field is extremely beneficial to work on my master’s and find a job after graduation.

Why study data science at Lake Forest College?

Other schools are a lot bigger, but when you have those bigger classrooms you don’t have the same connection with your professors. For example, with Professor Bousquet in his computational math course he actually goes around the classroom to each individual student and checks on them. We are able to have that one-on-one connection with the professor even in class. That connection really helps me identify where my weaknesses are in data science. My professor can correct me where I’m wrong and explain the correct way to approach the problem. It is also a pretty tightknit and collaborative community at the College, so all the data science majors are friends, which is really helpful because we all help each other with our codes, if we’re having trouble.