Systems and methods for throttling click bait

1. A computer-implemented method comprising:

creating, by a computing system, 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;

determining, by the computing system, a normalized factor value associated with a content item corresponding to a link based on information relating to the histogram;

predicting, by the computing system, whether the content item is likely click bait based on the normalized factor value associated with the content item;

determining, by the computing system, a value of a utility factor to be less than one when the content item corresponding to a link is predicted to be click bait;

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;

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; and

presenting, by the computing system, the content item to a user if a threshold is satisfied by the expected utility score associated with the content item.

2. The computer-implemented method of claim 1 , wherein the creating a histogram comprises:

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

3. The computer-implemented method of claim 1 , wherein the creating a histogram comprises:

creating buckets with each bucket having an associated time interval.

4. The computer-implemented method of claim 3 , wherein the creating a histogram comprises:

determining a center time for each bucket.

5. The computer-implemented method of claim 4 , wherein the creating a histogram comprises:

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.

6. The computer-implemented method of claim 1 , wherein the determining a value of a utility factor comprises:

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

7. The computer-implemented method of claim 6 , wherein the determining a value of a utility factor further comprises:

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.

8. 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:

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;

determining a normalized factor value associated with a content item corresponding to a link based on information relating to the histogram;

predicting whether the content item is likely click bait based on the normalized factor value associated with the content item;

determining a value of a utility factor to be less than one when the content item corresponding to a link is predicted to be click bait;

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

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; and

presenting, by the computing system, the content item to a user if a threshold is satisfied by the expected utility score associated with the content item.

9. The system of claim 8 , wherein the creating a histogram comprises:

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

10. The system of claim 8 , wherein the determining a value of a utility factor comprises:

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

11. 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:

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;

determining a normalized factor value associated with a content item corresponding to a link based on information relating to the histogram;

predicting whether the content item is likely click bait based on the normalized factor value associated with the content item;

determining a value of a utility factor to be less than one when the content item corresponding to a link is predicted to be click bait;

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

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; and

presenting, by the computing system, the content item to a user if a threshold is satisfied by the expected utility score associated with the content item.

12. The non-transitory computer-readable storage medium of claim 11 , wherein the creating a histogram comprises:

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

13. The non-transitory computer-readable storage medium of claim 11 , wherein the determining a value of a utility factor comprises:

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