PROVIDING RELEVANT NOTIFICATIONS BASED ON COMMON INTERESTS BETWEEN FRIENDS IN A SOCIAL NETWORKING SYSTEM

• US 20120166452A1
• Filed: 12/22/2010
• Published: 06/28/2012
• Est. Priority Date: 12/22/2010
• Status: Active Grant

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Tseng, Erick
• Granted Patent: US 8,560,678 B2
• Time in Patent Office: Days
• US Class Current: 707/749
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 65/40 Support for services or applications
• CPC Class Codes: H04L 65/403 Arrangements for multi-party communication, e.g. for conferences data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15

Abstract

A social networking system provides relevant third-party content objects to users by matching user location, interests, and other social information with the content, location, and timing associated with the content objects. Content objects are provided based on relevance scores specific to a user. Relevance scores may be calculated based on the user'"'"'s previous interactions with content object notifications, or based on interests that are common between the user and his or her connections in the social network. Context search is also provided for a user, wherein a list of search of results is ranked according to the relevance score of content object associated with the search results. Notifications may also be priced and distributed to users based on their relevance. In this way, the system can provide notifications that are relevant to user'"'"'s interests and current circumstances, increasing the likelihood that they will find content objects of interest.

Claims

1. A computer-implemented method for providing third-party content objects to a first user of a social network, the method comprising:

maintaining connections between users of the social networking system;

identifying a second user that is connected to the first user in the social network;

identifying an interest common to both the first user and the second user;

calculating a relevance score for a third-party content object associated with the common affinity based at least in part on a type of separation between the first user and the second user in the social network, the relevance score describing a measure of likelihood that the first user is interested in the third-party content object associated with the common interest; and

providing the third-party content object to a user device of the first user based at least in part on the inferred relevance score.

2. The computer-implemented method of claim 1, wherein the third-party content object comprises an informational content object describing one of movie show times, movie reviews, restaurant menus, restaurant reviews, product information, or product reviews associated with the common affinity.

3. The computer-implemented method of claim 1, wherein the third-party content object comprises an incentive content object describing one of coupons, discounts, promotions, or gift certificates associated with the common affinity.

4. The computer-implemented method of claim 1, wherein calculating the relevance score for the third-party content object comprises:

calculating a relevance score for the third-party content object relative to the second user, comprising;

determining a location value for the third-party content object, the location value based on a proximity between the location assigned to the third-party content object and a location associated with the second user;

determining an interest value for the third-party content object, the interest value based on whether a category assigned to the third-party content object is included in one or more categories associated with affinity information for the second user;

determining a time value for the third-party content object, the time value based on whether a current time is within the delivery time range assigned to the third-party content object;

determining a connection value for the third-party content object, the connection value based on a number of the second user'"'"'s plurality of connections associated with the third-party content object;

combining the location value, interest value, connection value, and time value to determine the relevance score; and

applying a weight to the relevance score to determine the relevance score for the first user, the weight based on the type of separation between the first user and the second user.

5. The computer-implemented method of claim 4, further comprising:

varying the weight applied to the relevance score based on the type of separation between the first user and the second user.

6. The computer-implemented method of claim 5, wherein the type of separation describes one or more degrees of separation between the first user and the second user in the social network.

7. The computer-implemented method of claim 1, wherein providing the identified third-party content object to the first user comprising:

providing the third-party content object in a search result responsive to a query from a client device of the first user.

8. The computer-implemented method of claim 1, wherein providing the identified third-party content object to the first user comprising:

automatically providing the third-party content object to a client device of the third user.

9. The computer-implemented method of claim 1, further comprising:

determining a list of third-party content objects for the first user based on interests of the first user and based on the common interest between the first user and the second user, the list comprising the third-party content object associated with the common interest.

10. The computer-implemented method of claim 1, further comprising:

re-ranking a list of third-party content objects to provide to the first user to include the third-party content object associated with the common interest based at least in part on the relevance score.

11. The computer-implemented method of claim 1, further comprising:

identifying an interest of the second user that is related to the common interest; and

calculating a relevance score for a second third-party content object associated with the interest of the second user; and

determining whether to provide the second third-party content object associated with the interest of the second user based on the relevance score.

20. The computer-implemented method of claim 1, further comprising:

identifying an interest of the second user that is related to the common interest;

calculating a relevance score for a second third-party content object associated with the interest of the second user; and

determining whether to provide the second third-party content object associated with the interest of the second user based on the relevance score.

12. A computer-implemented method for providing third-party content objects to a first user of a social network, the method comprising:

maintaining connections between users of the social networking system;

identifying a second user that is connected to the first user in the social network;

identifying an interest of the second user;

calculating a relevance score for a third-party content object associated with the interest of the second user based at least in part on a type of separation between the first user and the second user in the social network, the relevance score describing a measure of likelihood that the first user is interested in the third-party content object associated with the interest of the second user; and

storing the calculated relevance score in an account associated with the first user.

13. The computer-implemented method of claim 12, further comprising providing the third-party content object to the first user based at least in part on the relevance score.

14. The computer-implemented method of claim 12, wherein the third-party content object comprises an informational content object describing one of movie show times, movie reviews, restaurant menus, restaurant reviews, product information, or product reviews associated with the common affinity.

15. The computer-implemented method of claim 12, wherein the third-party content object comprises an incentive content object describing one of coupons, discounts, promotions, or gift certificates associated with the common affinity.

16. The computer-implemented method of claim 12, wherein calculating the relevance score for the third-party content object comprises:

calculating a relevance score for the third-party content object relative to the second user, comprising;

determining a location value for the third-party content object, the location value based on a proximity between the location assigned to the third-party content object and a location associated with the second user;

determining an interest value for the third-party content object, the interest value based on whether a category assigned to the third-party content object is included in one or more categories associated with affinity information for the second user;

determining a time value for the third-party content object, the time value based on whether a current time is within the delivery time range assigned to the third-party content object;

determining a connection value for the third-party content object, the connection value based on a number of the second user'"'"'s plurality of connections associated with the third-party content object;

combining the location value, interest value, connection value, and time value to determine the relevance score; and

applying a weight to the relevance score to determine the relevance score for the first user, the weight based on the type of separation between the first user and the second user.

17. The computer-implemented method of claim 16, further comprising:

varying the weight applied to the relevance score based on the type of separation between the first user and the second user.

18. The computer-implemented method of claim 17, wherein the type of separation describes one or more degrees of separation between the first user and the second user in the social network.

19. The computer-implemented method of claim 12, further comprising:

re-ranking a list of third-party content objects to provide to the first user to include the third-party content object associated with the common interest based at least in part on the relevance score.