SYSTEMS AND METHODS FOR THROTTLING CLICK BAIT

• US 20160188739A1
• Filed: 12/29/2014
• Published: 06/30/2016
• Est. Priority Date: 12/29/2014
• Status: Active Grant

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Tang, Joyce, El-Arini, Khalid Bakry, Vickrey, David
• Granted Patent: US 10,282,384 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/958 Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
• CPC Class Codes: G06Q 30/0271 Personalized advertisement
• CPC Class Codes: H04L 51/212 using filtering or selective blocking
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Systems, methods, and non-transitory computer readable media configured to determine a value of a utility factor associated with a content item corresponding to a link. An optimized utility value relating to an interaction type of an outbound click is determined based on the value of the utility factor. An expected utility score associated with the content item is generated based on the optimized utility value to determine potential presentation of the content item to a user.

Claims

1. A computer-implemented method comprising:

determining, by a computing system, a value of a utility factor associated with a content item corresponding to a link;

determining, by the computing system, an optimized utility value relating to an interaction type of an outbound click based on the value of the utility factor; and

generating, by the computing system, an expected utility score associated with the content item based on the optimized utility value to determine potential presentation of the content item to a user.

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

determining time durations of instances of consumption of the content item by members.

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

creating a histogram of count values relating to a number of members who consumed the content item based on a time duration of each instance of consumption of the content item by the members.

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

creating buckets with each bucket having an associated time interval.

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

determining a center time for each bucket.

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

determining for each bucket a count value relating to a number of members who consumed the content item over a time duration within a time interval associated with the bucket.

7. The computer-implemented method of claim 6, further comprising:

determining a normalized factor value associated with the content item based on the center time for each bucket and the count value for each bucket.

8. The computer-implemented method of claim 7, further comprising:

predicting the content item is likely click bait based on a distribution of normalized factor values associated with a plurality of content items, the distribution of normalized factor values including the normalized factor value associated with the content item.

9. The computer-implemented method of claim 7, further comprising:

performing a mapping to produce the value of the utility factor based on the normalized factor value associated with the content item.

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

based on the mapping, assigning the value of the utility factor to be less than one when the content item is predicted to be click bait.

11. A system comprising:

at least one processor; and

a memory storing instructions that, when executed by the at least one processor, cause the system to perform;

determining a value of a utility factor associated with a content item corresponding to a link;

determining an optimized utility value relating to an interaction type of an outbound click based on the value of the utility factor; and

generating an expected utility score associated with the content item based on the optimized utility value to determine potential presentation of the content item to a user.

12. The system of claim 11, further comprising:

determining time durations of instances of consumption of the content item by members.

13. The system of claim 11, further comprising:

creating a histogram of count values relating to a number of members who consumed the content item based on a time duration of each instance of consumption of the content item by the members.

14. The system of claim 11, further comprising:

determining a normalized factor value associated with the content item based on a center time for a bucket and a count value for the bucket.

15. The system of claim 14, further comprising:

performing a mapping to produce the value of the utility factor based on the normalized factor value associated with the content item.

16. A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform a method comprising:

determining a value of a utility factor associated with a content item corresponding to a link;

determining an optimized utility value relating to an interaction type of an outbound click based on the value of the utility factor; and

generating an expected utility score associated with the content item based on the optimized utility value to determine potential presentation of the content item to a user.

17. The non-transitory computer-readable storage medium of claim 16, further comprising:

determining time durations of instances of consumption of the content item by members.

18. The non-transitory computer-readable storage medium of claim 16, further comprising:

creating a histogram of count values relating to a number of members who consumed the content item based on a time duration of each instance of consumption of the content item by the members.

19. The non-transitory computer-readable storage medium of claim 16, further comprising:

determining a normalized factor value associated with the content item based on a center time for a bucket and a count value for the bucket.

20. The non-transitory computer-readable storage medium of claim 19, further comprising:

performing a mapping to produce the value of the utility factor based on the normalized factor value associated with the content item.