Sentiment Analysis of Washington Post News Articles

Analysis contains over 200,000 thousand web articles scraped from the Washington Post usinig Python and Selenium.
Articles are classified based on sentiment using KNN, SVMs, Neural Netorks, and more. Topic modeling is used to find general themes throughout the articles, and word clouds are composed for additional topic modeling insight.