PRODUCT REVIEW BIAS IDENTIFICATION AND RECOMMENDATIONS

• US 20120197816A1
• Filed: 01/24/2012
• Published: 08/02/2012
• Est. Priority Date: 01/27/2011
• Status: Abandoned Application

• Current Assignee: Electronic Entertainment Design And Research
• Original Assignee: Electronic Entertainment Design And Research
• Inventors: Short, Gregory T., Zatkin, Geoffrey C., Spence, Theodore, Divnich, Jesse, Hebard-Massey, Shane
• Application Number:
  US13/357,428
• Publication Number:
  US 20120197816A1
• Time in Patent Office: Days
• US Class Current: 705/347
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products

Abstract

Review bias identification systems and methods are presented. A bias in one or more review elements can be identified by deriving a measure of how a review outlet'"'"'s product review deviates from an industry average or composite review of the product. A bias engine generates a bias vector for a review outlet where the vector can include multiple bias metrics associated with one or more product properties. The bias engine can further present one or more recommendations of associating the product with a review outlet based on the bias vector.

Claims

1. A method of identifying a bias associated with product reviews, the method comprising:

providing access to a product database storing a plurality of product objects, the product objects each having product properties;

providing access to a review database storing a plurality of review objects, each review object representative of a product review of a product object and from a review outlet;

providing access to a bias engine communicatively coupled with the product database and the review database;

aggregating, by the bias engine, review scores derived from the review objects associated with one or more products having a common product property to form a composite review score;

generating, by the bias engine, a bias vector comprising bias metrics reflective of a review object'"'"'s deviation from the composite review score; and

configuring, by the bias engine, an output device to present a recommendation with respect to associating a product object with a review outlet based on the bias vector.

2. The method of claim 1, wherein the recommendation includes associating a product corresponding to the product object with the review outlet.

3. The method of claim 1, wherein recommendation includes avoiding association of a product corresponding to the product object with the review outlet.

4. The method of claim 1, wherein the composite review score comprise a vector having elements associated with one or more product properties.

5. The method of claim 1, wherein the bias vector comprises at least two elements.

6. The method of claim 1, wherein the product properties include genre, category, size, shape, color, awareness, and marketing spend.

7. The method of claim 1, further comprising weighting the review scores when forming the bias vector.

8. The method of claim 1, further comprising presenting the bias vector as a function of time.

9. The method of claim 1, wherein the recommendation includes review outlets most favorable to a product.

10. The method of claim 1, wherein the recommendation includes review outlets least favorable to a product.

11. The method of claim 1, further comprising presenting a favorability measure with respect to elements of the bias vector.

12. The method of claim 11, further comprising segmenting the favorability measure by a number of product properties.