DCInbox
SUMMARY:
SKILLS LEARNED:
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Scraped data from several thousand emails sent from Congresspeople, and analyzed this data using Python Natural Language Toolkit to yield insights that constituents can use when voting
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Designed a website that allows researchers to search a regularly-updated SQL database of all of the emails for a specific word or phrase, while also being able to sort by several parameters and visualize the data found
Check out the final product of our website here: dcinbox.com
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Python NLTK
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Gmail API
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Twitter API
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MatPlotLib
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Chart.js
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Node.js
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SQL
POSTER:
This project is best described through this poster that I designed for my school's research fair, which details the step-by-step process through which I accomplished my goal. Check out both posters from both years that I worked on this project!
CHALLENGES:
One challenge I faced the first year I worked on this project was that I was the sole Computer Science student on the team. The professor I worked for did not have much experience with coding, so she could not guide me through what I had to do. This gave me the opportunity to dive head-first into my work and motivated me to learn as much as I could. Though the overall task was daunting, I broke it into smaller parts that were seemed more accomplishable. With each small part came a new skill I picked up, and I felt proud of myself for teaching it to myself! My second year on this project, I was able to work with a team of other CS students. I loved the collaboration it took to create our final product!
Personal Note:
I was grateful to be on this team during my first summer in college, and get to return to it and a junior. I was excited to be able to apply my Computer Science skills to do data analysis on some very interested Political Science data. I loved the opportunity to teach myself and apply so many important concepts in NLP, such as scraping, stopwords, and more. I am still so proud of the end result of both summers of work!