Sentiment analysis is a popular technique in text mining that attempts to determine the emotional state of some text. We provide a new implementation of a common method for computing sentiment, whereby words are scored as positive or negative according to a dictionary lookup. Then the sum of those scores is returned for the document. We use the Hu and Liu sentiment dictionary (Hu and Liu, 2004) <doi:10.1145/1014052.1014073> for determining sentiment. The scoring function is vectorized by document, and scores for multiple documents are computed in parallel via OpenMP.