15. The computer-implemented method of claim 11 , wherein the sentences contained in the training data comprise sentences parsed from customer reviews for the category of items.
11. A computer-implemented method of extracting a quote regarding a relevant topic from customer reviews for a particular item, the method comprising executing instructions in a computer system to perform the operations of: receiving customer reviews for a category of items from a plurality of customers, wherein the category of items encompasses a particular item and items of a similar type; aggregating, by the computer system, the customer reviews for the category of items; parsing, by the computer system, a plurality of sentences from the customer reviews, wherein the parsing comprises breaking compound sentences in the customer reviews based on one or more of commas, coordinating conjunctions, or transition terms; classifying, by the computer system, the plurality of sentences by sentiment by utilizing a logistic regression classifier trained using sentiment scores of terms generated based on sentences contained in training data and manually labeled as to sentiment, wherein positive, negative and mixed sentiment scores of the terms are used as positive coefficients in the logistic regression classifier and neutral sentiment scores of the terms are used as negative coefficients in the logistic regression classifier; removing, by the computer system, those sentences having a neutral sentiment from the plurality of sentences; generating, by the computer system, a list of topics from the plurality of sentences utilizing latent Dirichlet allocation; assigning individual sentences in the plurality of sentences to a topic in the list of topics; selecting, by the computer system, the relevant topic from the list of topics for the particular item, wherein the relevant topic comprises the topic from the list of topics assigned to the most sentences parsed from the customer reviews regarding the particular item; selecting, by the computer system, a representative sentence from the plurality of sentences assigned to the relevant topic and parsed from the customer reviews regarding the particular item, the representative sentence having a highest relevance to the relevant topic and expressing a majority sentiment from among the plurality of sentences assigned to the relevant topic and parsed from the customer reviews regarding the particular item; and sending, by the computer system, the selected representative sentence to a customer computing device, wherein the selected representative sentence is presented to another customer on the customer computing device.