7. The method of claim 1 , further comprises: identifying a set of high-sentiment documents based on scoring sentiments expressed by one or more domain-specific documents; wherein creating the domain-specific sentiment lexicon comprises: identifying n-grams occurring within the documents in the set of high-sentiment documents; filtering the identified n-grams to remove n-grams unlikely to express sentiment in the specific specified domain; and storing the filtered n-grams as the domain-specific sentiment lexicon.
1. A method of constructing a domain-specific sentiment classifier for classifying sentiment expressed by documents in a specified domain, comprising: scoring sentiments expressed by one or more domain-specific documents, the scoring comprising: determining that one or more of the domain-specific documents include an n-gram, calculating a score for the n-gram included in the one or more domain-specific documents, and calculating a sentiment score for the one or more domain-specific documents based on the score for the n-gram included in the documents; creating a domain-specific sentiment lexicon based at least in part on said scoring sentiments expressed by one or more domain-specific documents; generating the domain-specific sentiment classifier based on the domain-specific sentiment lexicon; and storing the domain-specific sentiment classifier.