In this project, we look at how effective a support vector machine (SVM) is in classifying the political bias of a news article.  A  set of 15,000 articles was obtained and the bias was gauged using crowd-sourced information.  Articles were classified with a bias rating of “Far Right”, “Right”, “Unbiased”, “Left” or “Far Left”. The SVM performed well amongst the labels, with an average of 82% correct and slightly better Far Right classification results.