Methods and System for Social OnLine Association and Relationship Scoring

• US 20080120411A1
• Filed: 05/03/2007
• Published: 05/22/2008
• Est. Priority Date: 11/21/2006
• Status: Abandoned Application

• Current Assignee: Oliver Eberle
• Original Assignee: Oliver Eberle
• Inventors: Eberle, Oliver
• Application Number:
  US11/743,866
• Publication Number:
  US 20080120411A1
• Time in Patent Office: Days
• US Class Current: 709/225
• CPC Class Codes: G06Q 50/10 Services

Abstract

A method and system adopting mathematical and vastly in-depth analytical resources in order to evaluate, measure and ultimately place a unique and highly determinative score that provides information on such items as the quality of individual relationships in on line social networks and the context and characteristics of these relationships.

Claims

1. A method for obtaining a unique score for online relationships comprising:

collecting data; and

creating a first score, based upon said data, for online relationships between parties.

2. The method of claim 1, further comprising displaying a user'"'"'s social relationship score on the user'"'"'s profile page to identify the user'"'"'s trustworthiness and reliability.

3. The method of claim 1, further comprising filtering or blocking new users in social networks based on their social relationship score.

4. The method in claim 1, further comprising mapping user profiles and relationships of users between multiple social networks.

5. The method in claim 1 wherein a first score is used to create a second score for a party.

6. The method in claim 1 wherein vectors between parties are used to calculate a first score and a second score.

7. The method in claim 1 further comprising using third party opinion data to calculate a first score and a second score.

8. The method in claim 1 further comprising mapping user profiles and relationships of users between multiple social networks.

9. The method of claim 1 further comprising mapping user profiles and relationships of users according to quality of each particular relationship.

10. The method of claim 1 further comprising mapping user profiles and relationships of users according to the individuals involved in a particular relationship.

11. The method in claim 5 wherein a relationship context is used to create the second score.

12. The method in claim 5 wherein contextual relationship sub-scores are used to create the second score.

13. The method of claim 5 further comprising modifying the first score and the second score via anonymous data or private data.

14. The method of claim 5 further comprising modifying the first score and the second score via credit reports.

15. The method of claim 5 further comprising modifying the first score and the second score via logged anonymous data which later is identified with a particular individual or entity.

16. The method of claim 5 further comprising modifying the first score and the second score via ongoing user interactions.

17. The method of claim 1 further comprising gathering data about a user'"'"'s online relationships with individual and entities via a toolbar.

18. The method of claim 1 further comprising mining a user'"'"'s email history to extract relationships as well as the frequency, longevity, and depth of relationships.

19. A method online communication, comprising:

registering participants;

monitoring particpants'"'"' opinion data, quality of relationships, personal data, and credit reports;

creating a score based upon the data; and

weighting vectors associated with the data.

20. A method for obtaining a unique score for online relationships comprising:

collecting data; and

creating a first score, based upon said data, for online relationships between parties;

displaying a user'"'"'s social relationship score on the user'"'"'s profile page to identify the user'"'"'s trustworthiness and reliability;

filtering or blocking new users in social networks based on their social relationship score;

mapping user profiles and relationships of users between multiple social networks;

wherein a first score is used to create a second score for a party;

wherein vectors between parties are used to calculate a first score and a second score;

using third party opinion data to calculate a first score and a second score;

mapping user profiles and relationships of users between multiple social networks;

mapping user profiles and relationships of users according to quality of each particular relationship;

mapping user profiles and relationships of users according to the individuals involved in a particular relationship;

wherein a relationship context is used to create the second score;

wherein contextual relationship sub-scores are used to create the second score;

modifying the first score and the second score via anonymous data or private data;

modifying the first score and the second score via credit reports;

modifying the first score and the second score via logged anonymous data which later is identified with a particular individual or entity;

modifying the first score and the second score via ongoing user interactions;

gathering data about a user'"'"'s online relationships with individual and entities via a toolbar; and

mining a user'"'"'s email history to extract relationships as well as the frequency, longevity, and depth of relationships.