DETERMINING INFLUENCE IN A SOCIAL NETWORKING SYSTEM

• US 20160078478A1
• Filed: 11/20/2015
• Published: 03/17/2016
• Est. Priority Date: 11/28/2012
• Status: Active Grant

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Bosworth, Andrew G., Bharathi, Aruna
• Granted Patent: US 9,542,694 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 9/40 Network security protocols

Abstract

An influence metric describing the influence of a social networking system object on social networking system users is determined based on affinities between the users and the object. For example, affinities between the associated users and the object are combined to determine the influence metric. Content may be selected for presentation to users based in part on influence metrics of the content. Additionally, influence metrics of objects associated with a user may be combined to determine the relevance of objects associated with the user, which may also be used to select content for presentation to the user.

Claims

1. A method comprising:

storing, in a social networking system, a first set of associations between a plurality of users and a plurality of objects maintained by the social networking system, and a second set of associations between pairs of the plurality of users;

identifying a target object maintained by the social networking system;

identifying a first set of users associated with the target object from the stored first set of associations, the first set of users comprising a plurality of users;

determining a first set of affinities for the first set of users, the first set of affinities comprising an affinity for each of the first set of users for the target object;

identifying a second set of users associated with at least one of the first set of users from the stored second set of associations;

determining a second set of affinities for the second set of users, the second set of affinities comprising an affinity for each of the second set of users for at least one of the first set of users;

weighting at least one of the first set of affinities with the second set of affinities to produce a weighted set of affinities;

generating an influence metric associated with the target object based on the weighted set of affinities, the influence metric representing a relevance of the target object to the set of users as a whole; and

storing the influence metric.

2. The method of claim 1, wherein the target object comprises one of a user, a page, a group, or a content item.

3. The method of claim 1, wherein weighting at least one of the first set of affinities with the second set of affinities comprises determining a mean of the second set of affinities and weighting the at least one of the first set of affinities with the determined mean.

4. The method of claim 1, wherein each of the second set of users has previously established a connection with the at least one of the first set of users within the context of the social networking system.

5. The method of claim 1, further comprising weighting each of the first set of affinities with a different second set of affinities to produce the weighted set of affinities.

6. The method of claim 1, further comprising determining whether to present a story associated with the target object to one or more additional users based at least in part on the influence metric associated with the target object.

7. The method of claim 6, wherein the story comprises an action taken by a social networking system user in association with the target object.

8. A system comprising:

a non-transitory computer-readable storage medium storing executable computer instructions that, when executed by a processor, perform steps comprising;

storing a first set of associations between a plurality of users and a plurality of objects maintained by a social networking system, and a second set of associations between pairs of the plurality of users;

identifying a target object maintained by the social networking system;

identifying a first set of users associated with the target object from the stored first set of associations, the first set of users comprising a plurality of users;

determining a first set of affinities for the first set of users, the first set of affinities comprising an affinity for each of the first set of users for the target object;

identifying a second set of users associated with at least one of the first set of users from the stored second set of associations;

determining a second set of affinities for the second set of users, the second set of affinities comprising an affinity for each of the second set of users for at least one of the first set of users;

weighting at least one of the first set of affinities with the second set of affinities to produce a weighted set of affinities;

generating an influence metric associated with the target object based on the weighted set of affinities, the influence metric representing a relevance of the target object to the set of users as a whole; and

storing the influence metric; and

a hardware processor configured to execute the instructions.

9. The system of claim 8, wherein the target object comprises one of a user, a page, a group, or a content item.

10. The system of claim 8, wherein weighting at least one of the first set of affinities with the second set of affinities comprises determining a mean of the second set of affinities and weighting the at least one of the first set of affinities with the determined mean.

11. The system of claim 8, wherein each of the second set of users has previously established a connection with the at least one of the first set of users within the context of the social networking system.

12. The system of claim 8, wherein the instructions, when executed, perform further steps comprising weighting each of the first set of affinities with a different second set of affinities to produce the weighted set of affinities.

13. The system of claim 8, wherein the instructions, when executed, perform further steps comprising determining whether to present a story associated with the target object to one or more additional users based at least in part on the influence metric associated with the target object.

14. The system of claim 13, wherein the story comprises an action taken by a social networking system user in association with the target object.

15. A non-transitory computer-readable storage medium storing executable computer instructions that, when executed by a processor, perform steps comprising:

storing a first set of associations between a plurality of users and a plurality of objects maintained by a social networking system, and a second set of associations between pairs of the plurality of users;

identifying a target object maintained by the social networking system;

identifying a first set of users associated with the target object from the stored first set of associations, the first set of users comprising a plurality of users;

determining a first set of affinities for the first set of users, the first set of affinities comprising an affinity for each of the first set of users for the target object;

identifying a second set of users associated with at least one of the first set of users from the stored second set of associations;

determining a second set of affinities for the second set of users, the second set of affinities comprising an affinity for each of the second set of users for at least one of the first set of users;

weighting at least one of the first set of affinities with the second set of affinities to produce a weighted set of affinities;

generating an influence metric associated with the target object based on the weighted set of affinities, the influence metric representing a relevance of the target object to the set of users as a whole; and

storing the influence metric.

16. The computer-readable storage medium of claim 15, wherein the target object comprises one of a user, a page, a group, or a content item.

17. The computer-readable storage medium of claim 15, wherein weighting at least one of the first set of affinities with the second set of affinities comprises determining a mean of the second set of affinities and weighting the at least one of the first set of affinities with the determined mean.

18. The computer-readable storage medium of claim 15, wherein each of the second set of users has previously established a connection with the at least one of the first set of users within the context of the social networking system.

19. The computer-readable storage medium of claim 15, wherein the instructions, when executed, perform further steps comprising weighting each of the first set of affinities with a different second set of affinities to produce the weighted set of affinities.

20. The computer-readable storage medium of claim 15, wherein the instructions, when executed, perform further steps comprising determining whether to present a story associated with the target object to one or more additional users based at least in part on the influence metric associated with the target object.