SYSTEMS AND METHODS FOR CLASSIFYING CONTENT ITEMS BASED ON SOCIAL SIGNALS

1 . A computer-implemented method comprising:

determining, by a computing system, an initial classification for a content item based on one or more non-social signals associated with the content item;

determining, by the computing system, whether to monitor the content item based on the initial classification; and

determining, by the computing system, a subsequent classification for the content item based on at least one or more social signals associated with the content item after a determination to monitor the content item.

2 . The computer-implemented method of claim 1 , wherein the one or more non-social signals include one or more of: content attributes or user attributes.

3 . The computer-implemented method of claim 1 , further comprising training a first machine learning model based on non-social signals associated with a plurality of content items, and wherein the determining the initial classification for the content item is based on the first machine learning model.

4 . The computer-implemented method of claim 1 , wherein the one or more social signals include one or more of: comments or sentiment reactions.

5 . The computer-implemented method of claim 1 , further comprising training a second machine learning model based on social signals associated with a plurality of content items, and wherein the determining the subsequent classification for the content item is based on the second machine learning model.

6 . The computer-implemented method of claim 5 , wherein features for training the second machine learning model include one or more of: comment distribution, reaction distribution, comment content, or sharing distribution.

7 . The computer-implemented method of claim 1 , wherein the determining whether to monitor the content item based on the initial classification includes determining that a score for the content item associated with the initial classification satisfies a value or a range of values indicating uncertainty regarding whether the content item falls within the initial classification.

8 . The computer-implemented method of claim 7 , wherein the determining whether to monitor the content item is based on a third machine learning model.

9 . The computer-implemented method of claim 1 , wherein the initial classification and the subsequent classification indicate whether the content item is a particular type of content item.

10 . The computer-implemented method of claim 1 , wherein the determining the subsequent classification for the content item is triggered based on satisfaction of a specified criterion.

11 . A system comprising:

at least one hardware processor; and

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

determining an initial classification for a content item based on one or more non-social signals associated with the content item;

determining whether to monitor the content item based on the initial classification; and

determining a subsequent classification for the content item based on at least one or more social signals associated with the content item after a determination to monitor the content item.

12 . The system of claim 11 , wherein the one or more non-social signals include one or more of: content attributes or user attributes.

13 . The system of claim 11 , wherein the instructions further cause the system to perform training a first machine learning model based on non-social signals associated with a plurality of content items, and wherein the determining the initial classification for the content item is based on the first machine learning model.

14 . The system of claim 11 , wherein the one or more social signals include one or more of: comments or sentiment reactions.

15 . The system of claim 11 , wherein the instructions further cause the system to perform training a second machine learning model based on social signals associated with a plurality of content items, and wherein the determining the subsequent classification for the content item is based on the second machine learning model.

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

determining an initial classification for a content item based on one or more non-social signals associated with the content item;

determining whether to monitor the content item based on the initial classification; and

determining a subsequent classification for the content item based on at least one or more social signals associated with the content item after a determination to monitor the content item.

17 . The non-transitory computer readable medium of claim 16 , wherein the one or more non-social signals include one or more of: content attributes or user attributes.

18 . The non-transitory computer readable medium of claim 16 , wherein the method further comprises training a first machine learning model based on non-social signals associated with a plurality of content items, and wherein the determining the initial classification for the content item is based on the first machine learning model.

19 . The non-transitory computer readable medium of claim 16 , wherein the one or more social signals include one or more of: comments or sentiment reactions.

20 . The non-transitory computer readable medium of claim 16 , wherein the method further comprises training a second machine learning model based on social signals associated with a plurality of content items, and wherein the determining the subsequent classification for the content item is based on the second machine learning model.