Bazaarvoice, Inc.

Dustin Friesenhahn

Luveen Rupchand Wadhwani

Donald J Sedota, Jr

Dustin Mihalik

Brendan Sterne

A content intelligence module may implement a sentiment analysis method to identify words or phrases from user-generated content that are associated with a particular sentiment. The method may comprise grouping or splitting text into different sentiment segments, tokenizing words or phrases and/or removing stopwords across the sentiment segments, performing a frequency analysis to count the words or phrases in each sentiment segment, scaling the frequency results across the sentiment segments where necessary, and removing commonly used words from the sentiment segments. The words or phrases that are left in a specific sentiment segment are the most-used words for that sentiment segment. The word cloud module therefore allows for very quick generation of a summary around sentiment segments. A sentiment overview containing the summary can be presented to a user in connection with a selected product or service with which the user-generated content is associated.

System, method and computer program product for identifying words within collection of text applicable to specific sentiment

An overall average review rating for a product may be determined, based on user ratings that are associated with opinions of a product, within a dimension corresponding to a user trait. A segment variation score for each of a plurality of segments of the dimension may be determined. Each segment may correspond to one or more values of the user trait corresponding to the dimension. A total variation score may be determined for the dimension based on the segment variation scores determined for each of the plurality of segments of the dimension. The total variation score for the dimension may be compared to a polarization threshold to determine whether the dimension is polarized. Generated information may identify the product as having sentiment that is polarized.

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Austin, TX, United States of America

Dustin Friesenhahn