1. A computer-implemented method of classifying sentences as to sentiment, the method comprising executing instructions in a computer system to perform the operations of: acquiring training data comprising a plurality of sentences labeled as to sentiment; pre-processing the plurality of labeled sentences from the training data; generating a list of terms from the plurality of labeled sentences; determining sentiment scores for the terms in the list of terms utilizing a machine learning technique based on the plurality of labeled sentences; receiving a collection of sentences to be classified; pre-processing the collection of sentences; classifying each sentence from the collection of sentences as having a neutral sentiment or a non-neutral sentiment utilizing a first logistic regression classifier trained on the sentiment scores determined for the terms in the list of terms; and classifying each sentence having a non-neutral sentiment from the collection of sentences as having a positive sentiment or a negative sentiment by applying a second logistic regression classifier trained on the sentiment scores determined for the terms in the list of terms to determine a positive score for the sentence, applying a third logistic regression classifier trained on the sentiment scores determined for the terms in the list of terms to determine a negative score for the sentence, and combining the positive score and the negative score for the sentence.