ARRANGING STORIES ON NEWSFEED BASED ON EXPECTED VALUE SCORING ON A SOCIAL NETWORKING SYSTEM

• US 20160188607A1
• Filed: 03/10/2016
• Published: 06/30/2016
• Est. Priority Date: 12/14/2012
• Status: Active Grant

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Rubinstein, Dan Yigal, Vickrey, David, Cathcart, Robert William, Backstrom, Lars Seren, Thibaux, Romain Jean
• Granted Patent: US 11,487,769 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• 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: G06F 40/166 Editing, e.g. inserting or deleting
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A social networking system generates a newsfeed for a user to view when accessing the social networking system. Candidate stories associated with users of the social networking system are selected and an expected value score for each candidate story is determined. An expected value score is based on the probability of a user performing various types of interactions with a candidate story and a numerical value for each type of interaction. The numerical value for a type of interaction represents a value to the social networking system of the type of interaction. Based on the expected value scores, the candidate stories are ranked and the ranking used to select candidate stories for the newsfeed.

Claims

1. A method comprising:

receiving a request from a viewing user of an online system for posts associated with a plurality of other users of the online system;

selecting at least two candidate posts for the viewing user, the at least two candidate posts associated with one or more other users of the online system;

ranking the plurality of candidate posts for the viewing user;

determining an engagement level of each of the one or more other users associated with the candidate posts;

identifying, from the determined engagement levels, a less engaged user of the one or more other users, the less engaged user having an activity level below a threshold level;

determining, by a processor, a value to the online system of the viewing user interacting with a candidate post associated with the less engaged user;

modifying the ranking of the plurality of candidate posts for the viewing user, the modifying based at least in part on the value to the online system of the viewing user interacting with the candidate post associated with the less engaged user;

selecting a set of the candidate posts based at least in part on the modified ranking; and

sending the selected candidate posts for display to the viewing user.

2. The method of claim 1, wherein the activity level comprises a number of posts posted by the less engaged user.

3. The method of claim 1, wherein the activity level comprises a rate at which the less engaged user provides posts to the online system.

4. The method of claim 1, wherein the activity level comprises an amount of feedback received from other users of the online system on posts posted by the less engaged user.

5. The method of claim 4, wherein the feedback is selected from a group consisting of:

comments on a post, shares of a post, likes of a post, and hides of a post.

6. The method of claim 1, wherein the activity level comprises an elapsed time between a current time and a time when the less engaged user established an account with the online system.

7. The method of claim 1, wherein identifying the less engaged user comprises:

associating a neediness value with the less engaged user based on a comparison between the activity level of the less engaged user and the threshold.

8. The method of claim 7, wherein the neediness value is proportional to a difference between the activity level of the less engaged user and the threshold.

9. The method of claim 7, wherein increasing the ranking of the candidate post associated with the less engaged user comprises:

increasing the ranking of the candidate post by an amount based on the neediness value of the less engaged user.

10. The method of claim 1, wherein modifying the ranking of the plurality of candidate posts for the viewing user comprising increasing the ranking of the candidate post associated with the less engaged user.

11. The method of claim 1, further comprising, prior to modifying the ranking:

for each of the selected at least two candidate posts, determining a probability of the viewing user performing an interaction on the candidate post;

computing an expected value score for each of the selected at least two candidate posts, the expected value score based on;

(1) the determined probability of the viewing user performing the interaction on the candidate post, and

(2) the determined value to the online system of the viewing user performing the interaction on the candidate story; and

wherein modifying the ranking is based at least in part on the computer expected value score.

12. The method of claim 11, wherein modifying the ranking further comprises:

ranking the plurality of candidate posts such that candidate posts having higher expected value scores have a higher position in the ranking.

13. A computer program product comprising a computer readable storage medium having instructions encoded therein that, when executed by a processor, cause the processor to:

receive a request from a viewing user of an online system for posts associated with a plurality of other users of the online system;

select at least two candidate posts for the viewing user, the at least two candidate posts associated with one or more other users of the online system;

rank the plurality of candidate posts for the viewing user;

determine an engagement level of each of the one or more other users associated with the candidate posts;

identify, from the determined engagement levels, a less engaged user of the one or more other users, the less engaged user having an activity level below a threshold level;

determine, by a processor, a value to the online system of the viewing user interacting with a candidate post associated with the less engaged user;

modify the ranking of the plurality of candidate posts for the viewing user, the modifying based at least in part on the value to the online system of the viewing user interacting with the candidate post associated with the less engaged user;

select a set of the candidate posts based at least in part on the modified ranking; and

send the selected candidate posts for display to the viewing user.

14. The computer program product of claim 13, wherein the activity level comprises a rate at which the less engaged user provides posts to the online system.

15. The computer program product of claim 13, wherein the activity level comprises an amount of feedback received from other users of the online system on posts posted by the less engaged user.

16. The computer program product of claim 13, wherein the activity level comprises an elapsed time between a current time and a time when the less engaged user established an account with the online system.

17. The computer program product of claim 13, wherein the instructions that cause the processor to identify the less engaged user comprise further instructions that cause the processor to:

associate a neediness value with the less engaged user based on a comparison between the activity level of the less engaged user and the threshold.

18. The computer program product of claim 13, wherein modifying the ranking of the plurality of candidate posts for the viewing user comprising increasing the ranking of the candidate post associated with the less engaged user.

19. The computer program product of claim 13, further comprising instructions that cause the processor to, prior to modifying the ranking:

for each of the selected at least two candidate posts, determine a probability of the viewing user performing an interaction on the candidate post;

compute an expected value score for each of the selected at least two candidate posts, the expected value score based on;

(1) the determined probability of the viewing user performing the interaction on the candidate post, and

(2) the determined value to the online system of the viewing user performing the interaction on the candidate story; and

wherein modifying the ranking is based at least in part on the computer expected value score.

20. The computer program product of claim 19, wherein the instructions that cause the processor to modifying the ranking further comprise instructions to:

rank the plurality of candidate posts such that candidate posts having higher expected value scores have a higher position in the ranking.