Time-based sentiment analysis for product and service features
AssigneeInternational Business Machines Corporation
InventorsDhruv A. Bhatt, Kristin E. McNeil, Nitaben A. Patel
Life of this patent
Estimating the term…
Abstract
Provided are a method, computer program product and system for reporting time-based sentiment for a product. Text analysis is performed on at least one communication. At least one feature for the product is determined based on the text analysis. A sentiment value is generated for the at least one feature for the product. A date associated with the sentiment value is determined, and the sentiment value is reported for at least one feature over time.
Claims18
A computer implemented method for reporting sentiment of a product, comprising:
- performing a text analysis on communications, by at least one computing processor;
- determining at least one feature for the product based on the text analysis, by the at least one computing processor;
- generating sentiment values using the communications for the at least one feature for the product based on a sentiment dictionary and sentiment rules that determine a sentiment strength, by the at least one computing processor;
- determining a date associated with each of the sentiment values by extracting the date from the communications, by the at least one computing processor;
- for each date associated with each of the sentiment values, recording a feature annotation, a sentiment annotation, the sentiment value, metadata, and the date, wherein the feature annotation is generated using a feature dictionary and feature rules, and wherein the sentiment annotation is generated using the sentiment dictionary and the sentiment rules, by the at least one computing processor;
- and
- reporting how the sentiment values changed over time based on each date, by the at least one computing processor.
A system for reporting sentiment of a product, comprising:
- a processor;
- and
- a storage device connected to the processor, wherein the storage device has stored thereon a program, wherein the processor is configured to execute instructions of the program to perform operations, and wherein the operations comprise:
- performing a text analysis on communications;
- determining at least one feature for the product based on the text analysis;
- generating the sentiment values using the communications for the at least one feature for the product based on a sentiment dictionary and sentiment rules that determine a sentiment strength;
- determining a date associated with each of the sentiment values by extracting the date from the communications;
- for each date associated with each of the sentiment values, recording a feature annotation, a sentiment annotation, the sentiment value, metadata, and the date, wherein the feature annotation is generated using a feature dictionary and feature rules, and wherein the sentiment annotation is generated using the sentiment dictionary and the sentiment rules;
- and
- reporting how the sentiment values changed over time based on each date.
A computer program product for reporting sentiment of a product, the computer program product comprising:
- a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, executable by at least one processor of a computer is configured to perform:
- performing a text analysis on communications;
- determining at least one feature for the product based on the text analysis;
- generating the sentiment values using the communications for the at least one feature for the product based on a sentiment dictionary and sentiment rules that determine a sentiment strength;
- determining a date associated with each of the sentiment values by extracting the date from the communications;
- for each date associated with each of the sentiment values, recording a feature annotation, a sentiment annotation, the sentiment value, metadata, and the date, wherein the feature annotation is generated using a feature dictionary and feature rules, and wherein the sentiment annotation is generated using the sentiment dictionary and the sentiment rules;
- and
- reporting how the sentiment values changed over time based on each date.
Dependencies are inferred from the claim text.