1. A method for analyzing sentiment, comprising: at a first computer: dividing a collection of text into a plurality of sentiment segments; tokenizing words or phrases in the plurality of sentiment segments; performing a frequency analysis on tokenized words or phrases in each sentiment segment of the plurality of sentiment segments; performing a scaling operation to size individual sentiment segments based on results from the frequency analysis; for each tokenized word or phrase in each sentiment segment of the plurality of sentiment segments, subtracting a first number of the tokenized word or phrase in the sentiment segment from a second number of the tokenized word or phrase in at least one other sentiment segment of the plurality of sentiment segments, thereby producing, for each sentiment segment of the plurality of sentiment segments, a list of words or phrases that apply specifically to the sentiment segment; and providing the list of words or phrases that apply specifically to the sentiment segment to a second computer over a network connection.
1. A method for analyzing sentiment, comprising: at a first computer: dividing a collection of text into a plurality of sentiment segments; tokenizing words or phrases in the plurality of sentiment segments; performing a frequency analysis on tokenized words or phrases in each sentiment segment of the plurality of sentiment segments; performing a scaling operation to size individual sentiment segments based on results from the frequency analysis; for each tokenized word or phrase in each sentiment segment of the plurality of sentiment segments, subtracting a first number of the tokenized word or phrase in the sentiment segment from a second number of the tokenized word or phrase in at least one other sentiment segment of the plurality of sentiment segments, thereby producing, for each sentiment segment of the plurality of sentiment segments, a list of words or phrases that apply specifically to the sentiment segment; and providing the list of words or phrases that apply specifically to the sentiment segment to a second computer over a network connection. 7. The method of claim 1 , wherein the plurality of sentiment segments comprises a positive sentiment and a negative sentiment.