Separating the Senate [OPEN]
About me: My name is Alex, a graduate student who is looking to use PCA/other statistical tools to quantify partisanship in the Senate, inspired by this (https://nicogj.github.io/post/2018/02/13/senate-polarization.html).
Problem Definition - Given the increase in political polarization and partisanship in Congress and outside of it, how can we quantify these differences? How can we quantify the change in polarization over time?
Data - We'll be using senator vote records scraped from the internet that I have already collected and cleaned (though it can totally be extended!)
Deliverable - I hope to create a set of visualizations and write a blog post of our process and discussion about our results (since I am not a Poli Sci student and I imagine most of you aren't either, this can totally be in the realm of speculation.
Timeline - N/A yet
Team - I am currently working alone, but am excited to meet potential team members! Comment if you're interested :)
5 Comments
Hi! I am super interested in learning more about this project! I am passionate about data science and have always been curious about politics. I would love to be able to link these and use data science to further investigate partisanship. My email is rachelmccarty@berkeley.edu, hope to hear from you!
Hi there! I am Vaidehi, an inteded economics and data science major at UC Berkeley. I have some experience using R and Python for data analysis and visualization. I've also worked on a project similar to yours before, in which I used multivariate linear regression to look at the different variables that are correlated with political polarization. I think your project idea is really interesting and would love to be a part of it. You can contact me at vaidehi-b@berkeley.edu. Thanks!
Hi Alex. My name is Paul and I'm an undergrad studying data science. I've taken DATA100 (Principles and Techniques of Data Science) which gave practical experience using Pandas, SciKits, and NumPy for data analysis and visualizations. I also have experience in Python from both DATA100 and lower division courses. Your project idea is very intriguing, and I can help speculate about events or specific trends that contributed to the growing partisanship in politics. I briefly considered becoming a Poli Sci major because I like reading about international affairs and the role of America in the world. My email is p.terrellperica@berkeley.edu if you want to get in contact or discuss more. Thank you.
Hello! My name is George and I am an undergrad studying computer science with an emphasis in machine learning. I've taken EECS 127 (Intro to Convex Optimization) and Stat 134 (Probability in Statistics). I also have plenty of coding experience (from CS61a/b) in addition to being super interested in political polarization (I've read Jon Haidt's "The Coddling of the American Mind" and am in the middle of reading his "The Righteous Mind"). My email is georgegarcia846@berkeley.edu if you want to get in contact. Thanks for your consideration!
Hello! My name is Melissa and I am a Thai-American undergrad studying economics (with possibly either East Asian Languages and Cultures or Computer Science). I've taken statistics and coding classes at UC Berkeley as well as political science classes. I've also done political internships in the past and enjoy reading political work. As an experienced writer I would definitely be up to write that blog post. I'm enthusiastic about earning more experience in data analytics. I can go into more detail at mbunna@berkeley.edu. Thanks for your consideration!