Topic Modeling, Topic Noise Modeling, Unsupervised Learning, Twitter Data, Text Data.
distribution. When we go to finalize topics, we look at each topic individually and decide whether each word belongs in that topic or in noise. We decide based on a word’s frequency in the topic and noise distributions. We can think of it as a scale, where one side is weighted by topic frequency