Topic models provide a simple way to analyze large volumes of unlabeled text. A "topic" consists of a cluster of words that frequently occur together. Using contextual clues, topic models can connect words with similar meanings and distinguish between uses of words with multiple meanings. For a general introduction to topic modeling, see for example Probabilistic Topic Models by Steyvers and Griffiths (2007).