Granted Patent B2

US 10,936,959 · App. 16/182,839 · Granted Mar 2, 2021

Abstract

Claims (64)

1. A method comprising:

analyzing, using one or more computer processors, each of a plurality of documents related to a person to identify content attributes that occur in a dictionary for behavior or personality traits;

calculating, using the one or more computer processors, an initial score for each behavior and personality trait related to the identified content attributes;

calculating, using the one or more computer processors, trait metrics for each behavior or personality trait by combining initial scores for each behavior or personality trait;

providing, using the one or more computer processors, the trait metrics as input to a rule based scoring and machine learning system;

obtaining, from the rule based scoring and machine learning system, a trustworthiness score of the person output from the rule based scoring and machine learning system;

receiving an indication that a second person trusts the person;

creating a relationship between the second person and the person; and

adjusting the trustworthiness score of the person based on, at least, a trustworthiness score of the second person.

2. The method of claim 1 , wherein calculating an initial score for each behavior and personality trait related to the identified content attributes is based on weights associated with the identified content attributes.

3. The method of claim 1 , wherein analyzing each of the plurality of documents to identify content attributes comprises identifying one or more portions of each document that contain text authored by the person or that provide information about the person.

4. The method of claim 1 , further comprising:

determining that the trustworthiness score is not accurate; and

retraining the rule based scoring and machine learning system to correct for the inaccuracy using the trait metrics.

5. The method of claim 2 , wherein a behavior or personality trait includes at least one of a group comprising: badness, anti-social tendencies, goodness, conscientiousness, openness, extraversion, agreeableness, neuroticism, narcissism, Machiavellianism, and psychopathy.

6. The method of claim 1 , wherein a behavior or personality trait includes at least one of a group comprising: creating a false or misleading online profile or providing false or misleading information to a service provider, involvement with drugs or alcohol, involvement with hate websites or organizations, involvement in sex work, involvement in a crime, involvement in civil litigation, being a known fraudster or scammer, involvement in pornography, and authoring online content with negative language.

7. The method of claim 1 , wherein calculating an initial score for each behavior and personality trait related to the identified attributes is based on an identity score for each of the plurality of documents.

8. The method of claim 7 , wherein the identity score for each of the plurality of documents is calculated by:

identifying identity information within each document of the plurality of documents;

determining the uniqueness of the identify information identified within each document of the plurality of documents; and

calculating the identity score for each of the plurality of documents based on matching one or more identification attributes of the person to the identity information in each document of the plurality of documents and the uniqueness of the identity information.

9. The method of claim 8 , further comprising:

determining that at least one document comprises new identity information;

determining whether the identity score for the at least one document exceeds a predetermined threshold; and

based on determining that the identity score for the at least one document exceeds a predetermined threshold, adding the new identity information to the identification attributes of the person.

10. The method of claim 9 , further comprising the steps of:

determining whether user input identification attributes are authentic by determining if the identity information of the person contained in one or more documents of the plurality of documents is consistent with the user input identification attributes; and

calculating the trait metrics based on determining that the user input identification attributes are authentic.

11. A computing system comprising:

a memory that stores instructions; and

one or more processors configured by the instructions to perform operations comprising:

analyzing each of a plurality of documents related to a person to identify content attributes that occur in a dictionary for behavior or personality traits;

calculating an initial score for each behavior and personality trait related to the identified content attributes;

calculating trait metrics for each behavior or personality trait by combining initial scores for each behavior or personality trait;

providing the trait metrics as input to a rule based scoring and machine learning system;

obtaining, from the rule based scoring and machine learning system, a trustworthiness score of the person output from the rule based scoring and machine learning system;

receiving an indication that a second person trusts the person;

creating a relationship between the second person and the person; and

adjusting the trustworthiness score of the person based on, at least, a trustworthiness score of the second person.

12. The computing system of claim 11 , wherein calculating an initial score for each behavior and personality trait related to the identified content attributes is based on weights associated with the identified content attributes.

13. The computing system of claim 11 , wherein analyzing each of the plurality of documents to identify content attributes comprises identifying one or more portions of each document that contain text authored by the person or that provide information about the person.

14. The computing system of claim 11 , further comprising:

determining that the trustworthiness score is not accurate; and

retraining the rule based scoring and machine learning system to correct for the inaccuracy using the trait metrics.

15. The computing system of claim 12 , wherein a behavior or personality trait includes at least one of a group comprising: badness, anti-social tendencies, goodness, conscientiousness, openness, extraversion, agreeableness, neuroticism, narcissism, Machiavellianism, and psychopathy.

16. The computing system of claim 11 , wherein a behavior or personality trait includes at least one of a group comprising: creating a false or misleading online profile or providing false or misleading information to a service provider, involvement with drugs or alcohol, involvement with hate websites or organizations, involvement in sex work, involvement in a crime, involvement in civil litigation, being a known fraudster or scammer, involvement in pornography, and authoring online content with negative language.

17. The computing system of claim 11 , wherein calculating an initial score for each behavior and personality trait related to the identified attributes is based on an identity score for each of the plurality of documents.

18. The computing system of claim 17 , wherein the identity score for each of the plurality of documents is calculated by:

identifying identity information within each document of the plurality of documents;

determining the uniqueness of the identify information identified within each document of the plurality of documents; and

calculating the identity score for each of the plurality of documents based on matching one or more identification attributes of the person to the identity information in each document of the plurality of documents and the uniqueness of the identity information.

19. The computing system of claim 18 , further comprising:

determining that at least one document comprises new identity information;

determining whether the identity score for the at least one document exceeds a predetermined threshold; and

based on determining that the identity score for the at least one document exceeds a predetermined threshold, adding the new identity information to the identification attributes of the person.

20. A non-transitory computer-readable medium comprising instruction stored thereon that are executable by at least one processor to cause a computing device to perform operations comprising:

analyzing each of a plurality of documents related to a person to identify content attributes that occur in a dictionary for behavior or personality traits;

calculating an initial score for each behavior and personality trait related to the identified content attributes;

calculating trait metrics for each behavior or personality trait by combining initial scores for each behavior or personality trait;

providing the trait metrics as input to a rule based scoring and machine learning system;

obtaining, from the rule based scoring and machine learning system, a trustworthiness score of the person output from the rule based scoring and machine learning system;

receiving an indication that a second person trusts the person;

creating a relationship between the second person and the person; and

adjusting the trustworthiness score of the person based on, at least, a trustworthiness score of the second person.

Assignments (8)