EMOTION IDENTIFICATION SYSTEM AND METHOD

• US 20140095150A1
• Filed: 03/15/2013
• Published: 04/03/2014
• Est. Priority Date: 10/03/2012
• Status: Abandoned Application

• Current Assignee: Kanjoya, Inc. (Seahawk Acquisition Corp.)
• Original Assignee: Kanjoya, Inc. (Seahawk Acquisition Corp.)
• Inventors: Berjikly, Armen, Sudhof, Moritz, Sheth, Neil, Garapaty, Kumar
• Application Number:
  US13/844,522
• Publication Number:
  US 20140095150A1
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30

Abstract

A system and method for identifying emotion in text that connotes authentic human expression, and training an engine that produces emotional analysis at various levels of granularity and numerical distribution across a set of emotions at each level of granularity. The method may include producing a chart of data transmissions referenced against time, comparing filtered data transmissions to a database, and selecting a database based on a demographic class of an author.

Claims

1. A method of producing a chart of data transmissions referenced against time comprising:

providing, with a processor, a database of data indicators that each define emotional content of textual data;

receiving, at a processor, a plurality of textual data transmissions sent by at least one individual during a span of time;

processing, with a processor, the plurality of textual data transmissions to produce at least one data indicator defining emotional content of the plurality of textual data transmissions;

inputting, with a processor, the at least one data indicator of the plurality of textual data transmissions into an emotion similarity model and the data indicators of the database into the emotion similarity model to determine at least one similarity between the at least one data indicator of the plurality of textual data transmissions and the data indicators of the database; and

producing, with a processor, a chart displaying at least one value corresponding to the at least one similarity referenced against at least a portion of the span of time.

2. The method of claim 1, wherein the textual data of the database has been authored by at least one individual on a webpage of an online forum system.

3. The method of claim 2, wherein the textual data of the database has been tagged with at least one tag by an author of the textual data, the at least one tag being associated with at least one emotion and associating at least a portion of the textual data of the database with the at least one emotion.

4. The method of claim 1, wherein the at least one data indicator is produced using textual analysis selected from a group consisting of latent semantic analysis, and positive pointwise mutual information.

5. The method of claim 1, wherein the emotion similarity model is selected from a group consisting of a support vector machine model, a naï

ve Bayes model, and a maximum entropy model.

6. The method of claim 1, wherein the chart is a line graph.

7. The method of claim 1, wherein the at least one value corresponding to the at least one similarity is displayed as a function of the at least a portion of the span of time.

8. The method of claim 1, wherein an individual may select to display a portion of the span of time on the chart and to not display a portion of the span of time on the chart.

9. The method of claim 1, further comprising allowing an individual to not display on the chart at least one value corresponding to at least one similarity produced by the inputting step, based on a word contained within a textual data transmission corresponding to the at least one value that is not displayed.

10. The method of claim 1, wherein the chart is produced in real time.

11. The method of claim 1, wherein the plurality of textual data transmissions are sent by at least one individual using a mobile device.

12. A method of comparing filtered data transmissions to a database comprising:

providing, with a processor, a database of data indicators that each define emotional content of textual data;

receiving, at a processor, a plurality of textual data transmissions sent by at least one individual;

filtering, with a processor, the plurality of textual data transmissions to produce a subset of the plurality of textual data transmissions based on whether words of the plurality of textual data transmissions contain at least one specified word;

processing, with a processor, the subset of the plurality of textual data transmissions to produce at least one data indicator defining emotional content of the subset of the plurality of textual data transmissions; and

inputting, with a processor, the at least one data indicator of the subset of the plurality of textual data transmissions into an emotion similarity model and the data indicators of the database into the emotion similarity model to determine at least one similarity between the at least one data indicator of the subset of the plurality of textual data transmissions and the data indicators of textual data of the database.

13. The method of claim 12, wherein the textual data of the database has been authored by at least one individual on a webpage of an online forum system.

14. The method of claim 13, wherein the textual data of the database has been tagged with at least one tag by an author of the textual data, the at least one tag being associated with at least one emotion and associating at least a portion of the textual data of the database with the at least one emotion.

15. The method of claim 12, wherein the at least one specified word is selected from a group consisting of:

a commercial service, a commercial product, the name of an individual, and combinations thereof.

16. A method of selecting a database based on a demographic class of an author comprising:

providing, with a processor, a first database of data indicators that each define emotional content of textual data and are associated with a first demographic class;

providing, with a processor, a second database of data indicators that each define emotional content of textual data and are associated with a second demographic class;

receiving, at a processor, first textual data authored by a first individual who is associated with the first demographic class;

processing, with a processor, the first textual data to produce a first data indicator defining emotional content of the first textual data;

receiving, at a processor, second textual data authored by a second individual who is associated with the second demographic class;

processing, with a processor, the second textual data to produce a second data indicator defining emotional content of the second textual data;

determining, with a processor, whether to input the first data indicator into a first emotion similarity model that utilizes the data indicators of the first database, or into a second emotion similarity model that utilizes the data indicators of the second database, based on whether the first individual is associated with the first demographic class or the second demographic class;

inputting, with a processor, the first data indicator into the first emotion similarity model to determine a similarity between the first textual data and the data indicators of the first database; and

inputting, with a processor, the second data indicator into the second emotion similarity model to determine a similarity between the second textual data and the data indicators of the second database.

17. The method of claim 16, wherein the first individual is a user of the online forum system, and the online forum system stores demographic information about the first individual indicating that the first individual is associated with the first demographic class.

18. The method of claim 17, wherein the demographic information stored includes the first individual'"'"'s sex, age and geographic area of residence.

19. The method of claim 16, wherein the textual data of the first database has been tagged with at least one tag by an author of the textual data of the first database, the at least one tag being associated with at least one emotion and associating at least a portion of the textual data of the first database with the at least one emotion.

20. The method of claim 16, further comprising determining, with a processor, whether to input the second data indicator into the first emotion similarity model, or into the second emotion similarity model, based on whether the second individual is associated with the first demographic class or the second demographic class.