IP Library Granted Patent US 8,775,605
Granted Patent B2
US 8,775,605 · App. 12/892,208 · Granted Jul 8, 2014

Method and apparatus to identify outliers in social networks

Inventor: Balachander Krishnamurthy (New York, NY)
Assignee: AT&T Intellectual Property I, L.P.
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Quick Facts
Patent No.
US 8,775,605
App. No.
12/892,208
Granted
Jul 8, 2014
Kind
B2
Abstract

A system that incorporates teachings of the present disclosure may include, for example, a computing device having an interface for receiving seed information, and a controller to identify one or more outliers from a reduced sampling of a total population of on-line social network (OSN) users according to the seed information and at least one of a social graph or a generalization of portions of the total population of OSN users. Additional embodiments are disclosed.

Claims (36)

1. A method, comprising:

obtaining, by a system comprising a processor, seed information, wherein the seed information comprises privacy profile settings of one of on-line social network users or groups of on-line social networks;

comparing, by the system, the seed information to a random population of on-line social network users, resulting in a comparison;

reducing, by the system, a sampling size of a total population of on-line social network users according to the comparison of the seed information, resulting in a reduced sampling of on-line social network users;

comparing, by the system, the reduced sampling of on-line social network users to one of a social graph, a generalized profile of on-line social network users determined from the total population of on-line social network users, or a combination thereof;

determining the social graph from a Metropolis-Hastings Algorithm applied to an on-line social network of the on-line social network users or groups of on-line social networks; and

identifying, by the system, an outlier in the reduced sampling of on-line social network users based on relationships between the on-line social network users, wherein the outlier does not conform to one of the social graph or the generalized profile of on-line social network users for use by equipment of a law enforcement agency.

2. The method of claim 1 , wherein the seed information further comprises one of geographic information, behavioral pattern information, or user information.

3. The method of claim 1 , wherein the seed information further comprises information associated with the on-line social network users having a relation to a party who may not be an on-line social network user.

4. The method of claim 1 , comprising determining, by the system, the social graph from a crawl procedure applied to the on-line social network.

5. The method of claim 1 , wherein obtaining the seed information comprises receiving from a third party the seed information, and wherein the method further comprises receiving one of the social graph, or the generalized profile.

6. A computing device, comprising:

a memory that stores executable instructions;

an interface for receiving seed information; and

a controller coupled to the memory, wherein execution of the instructions by the controller facilitates performance of operations comprising:

receiving the seed information from equipment of a law enforcement agency, wherein the seed information comprises privacy profile settings of one of on-line social network users or groups of on-line social networks;

comparing the seed information to a random population of on-line social network users to obtain a comparison;

identifying an outlier from a reduced sampling of a total population of on-line social network users based on relationships between the on-line social network users, the comparison and one of a social graph or a generalization of portions of the total population of on-line social network users for use by the equipment of the law enforcement agency;

determining the social graph from a Metropolis-Hastings Algorithm applied to an on-line social network of the on-line social network users or groups of on-line social networks;

determining one of the social graph or the generalization from the total population of on-line social network users; and

comparing the random population of on-line social network users to one of the social graph or the generalization to determine the outlier.

7. The computing device of claim 6 , wherein the seed information further comprises one of geographic information, behavioral pattern information, or user information.

8. The computing device of claim 6 , wherein the seed information further comprises information associated with on-line social network users having a relation to a party who may not be an on-line social network user.

9. The computing device of claim 6 , wherein the operations further comprise determining the social graph from a crawl procedure applied to the on-line social network.

10. The computing device of claim 6 , wherein the social graph indicates one of a type of user communication, a content type or a user action.

11. A non-transitory machine-readable storage medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations comprising:

obtaining seed information from equipment of a law enforcement agency, wherein the seed information comprises privacy profile settings of one of on-line social network users or groups of on-line social networks;

comparing the seed information to a random population of on-line social network users, resulting in a comparison;

reducing a sampling size of a population of the on-line social network users according to the comparison of the seed information, resulting in a reduced sampling of on-line social network users;

determining a social graph from a Metropolis-Hastings Algorithm applied to an on-line social network of the on-line social network users or groups of on-line social networks;

comparing the reduced sampling of on-line social network users to one of a social graph, a generalized profile of on-line social network users determined from a total population of on-line social network users, or a combination thereof; and

identifying an outlier in the reduced sampling of on-line social network users based on relationships between the on-line social network users that do not conform to one of the social graph or the generalized profile of on-line social network users for use by equipment of a law enforcement agency.

12. The non-transitory machine-readable storage medium of claim 11 , wherein the seed information further comprises one of geographic information, behavioral pattern information, or user information.

13. The non-transitory machine-readable storage medium of claim 11 , wherein the seed information further comprises information associated with on-line social network users having a relation to a party who may not be an on-line social network user.

14. The non-transitory machine-readable storage medium of claim 11 , wherein obtaining the seed information comprises receiving the seed information from a third party, and wherein the operations further comprise receiving one of the social graph, or the generalized profile.

15. The non-transitory machine-readable storage medium of claim 11 , wherein the social graph indicates one of a type of user communication, a content type or a user action.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 28, 2010
From: KRISHNAMURTHY, BALACHANDER
To: AT&T INTELLECTUAL PROPERTY I, L.P.
Reel/Frame 025053/0720 →
Continuity (2)
Provisional Application 61246897 · Sep 29, 2009
Related Publication 20110078306A1 · Mar 31, 2011