In this work contains a two-part system for sentiment analysis and topic modeling of tweets. In our system, tweets are classified as either “positive”, “negative”, or “neutral” sen- timent-bearing. The tweets are then sorted into document groups based on the search term used to retrieve the tweet and sent to an LDA topic modeling subsystem to extract words/topics related to the respective search terms.