Slang is a continuously evolving phenomenon of language.The rise of social media has resulted in numerous slang terms circulating across the globe. In this paper, we aim to find novel and creative slang in the comments sections of online political news articles covering the 2016 US Presidential Election. First, we define creative political slang and partition it into sub-classes. Next, we extract a dataset of partisan news articles and comments ranging from the left wing to the right wing. Then, we develop PoliSlang, an unsupervised algorithm for detecting creative slang, evaluating its performance using expert human judgments. Finally, we use this algorithm to compare and contrast political slang usage by commenters across different news media.