Determining influence in a social networking system

• US 9,224,174 B2
• Filed: 11/28/2012
• Issued: 12/29/2015
• 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
• Primary Examiner(s): Golabbakhsh, Ebrahim
• Application Number:
  US13/688,015
• Publication Number:
  US 20140149503A1
• Time in Patent Office: 1,126 Days
• Field of Search: 709/204, 709/205, 709/206, 709/207, 709/223, 707/802, 705/1.1, 705/7.14
• 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, associations between a plurality of users and a plurality of objects maintained by the social networking system;

identifying a target object maintained by the social networking system;

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

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

generating an influence metric associated with the target object based on the set of affinities by applying a weight to each of the set of affinities to generate weighted affinities and by determining a mean of the weighted 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 a weight applied to an affinity is based at least in part on a characteristic of a user associated with the affinity.

4. The method of claim 3, wherein the characteristic is a time of a most recent interaction between the user and the target object.

5. The method of claim Oil 1, wherein generating the influence metric based on the weighted affinities further comprises:

determining a median of the weighted affinities.

6. A method comprising:

identifying a target object maintained by a social networking system;

identifying a set of users associated with the target object based on stored information describing interactions performed by users and connections between users and objects maintained by the social networking system;

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

generating an influence metric associated with the target object based on the set of affinities by applying a weight to each of the set of affinities to generate weighted affinities and by determining a mean of the weighted affinities, the influence metric representing a relevance of the target object to the set of users as a whole; and

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 determining whether to present the 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 comprises:

transmitting a notification message describing the story to an additional user if the influence metric associated with the target object is at least a threshold value.

8. The method of claim 6, wherein determining whether to present the 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 comprises:

determining whether to present the story associated with the target object to an additional user based on a location associated with the additional user, a location associated with the target object, and the influence metric associated with the target object.

9. The method of claim 6, wherein a weight applied to an affinity is based at least in part on a characteristic of a user associated with the affinity.

10. A method comprising:

identifying a target object maintained by a social networking system;

identifying a set of users associated with the target object based on stored information describing interactions performed by users and connections between users and objects maintained by the social networking system;

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

generating an influence metric associated with the target object based on the affinities by applying a weight to each of the set of affinities to generate weighted affinities and by determining a mean of the weighted affinities, the influence metric representing a relevance of the target object to the identified users as a whole;

identifying an advertisement associated with the target object; and

determining whether to present the advertisement 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.