Analyzing, classifying, and restricting user-defined hashtags

Abstract

The present disclosure relates to systems, non-transitory computer-readable media, and methods for customizing a set of restrictions for a hashtag or other user-defined annotation that violates guidelines or rules of an online resource based on automated and manual review. In particular, in one or more embodiments, the disclosed systems trigger manual review of user-defined annotations in a social networking system, determine various metrics based on both manual and automated review of content including a particular user-defined annotation, and generate a customized set of restrictions for the user-defined annotation based on those metrics. More specifically, the system can generate and utilize various manual review metrics and a moderated media metric to generate a custom set of restrictions for a user-defined annotation.

What is claimed is: 
     
         1 . A method comprising:
 triggering a manual review of media associated with a user-defined hash-tag via a review system;   generating a representative set of content items associated with the user-defined hash-tag, wherein the representative set of content items comprises a plurality of content items;   determining, via the review system and from the representative set of content items, a first plurality of content items that include the user-defined hash-tag and have top numbers of user engagements;   determining, via the review system and from the representative set of content items, a second plurality of content items that include the user-defined hash-tag and were posted most recently; and   providing the first plurality of content items and the second plurality of content items together via a review graphical user interface.   
     
     
         2 . The method of  claim 1 , further comprising:
 generating, based on a manual review of the representative set of content items via the review graphical user interface, one or more manual review metrics; and   analyzing media moderation associated with the user-defined hash-tag to determine a moderated media metric associated with the user-defined hash-tag.   
     
     
         3 . The method of  claim 2 , wherein analyzing the media moderation comprises determining a percent of media comprising the user-defined hash-tag deleted for violating one or more guidelines, terms, and/or conditions of a social networking system. 
     
     
         4 . The method of  claim 2 , further comprising customizing a set of restrictions for the user-defined hash-tag utilizing the one or more manual review metrics and the moderated media metric. 
     
     
         5 . The method of  claim 4 , wherein customizing the set of restrictions for the user-defined hash-tag comprises:
 determining that a total violation score reflecting a total percentage of violation of the media from the manual review for the user-defined hash-tag is above a total violation threshold;   determining that a recent violation score reflecting a percentage of violation of recent media from the manual review for the user-defined hash-tag is above a recent violation threshold;   determining that the moderated media metric is above a moderated media threshold; and   selecting a block restriction for the user-defined hash-tag.   
     
     
         6 . The method of  claim 4 , wherein customizing the set of restrictions for the user-defined hash-tag comprises:
 determining that a total violation score reflecting a total percentage of violation of the media from the manual review for the user-defined hash-tag is above a total violation threshold;   determining that a recent violation score reflecting a percentage of violation of recent media from the manual review for the user-defined hash-tag is below a recent violation threshold;   determining that the moderated media metric is below a moderated media threshold; and   selecting a modified content page restriction for the user-defined hash-tag, wherein the modified content page restriction comprises an expiration.   
     
     
         7 . The method of  claim 2 , wherein generating the one or more manual review metrics comprises utilizing the representative set of content items to generate at least one of a violation percentage for top media associated with the user-defined hash-tag, a violation percentage for recent media associated with the user-defined hash-tag, or an overall violation percentage for media associated with the user-defined hash-tag. 
     
     
         8 . The method of  claim 1 , further comprising generating, for the user-defined hash-tag, a positive classification, a neutral classification, or a negative classification. 
     
     
         9 . The method of  claim 8 , further comprising:
 determining a prior classification associated with the user-defined hash-tag; and   customizing the manual review based on the prior classification.   
     
     
         10 . A computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:
 triggering a manual review of media associated with a user-defined hash-tag via a review system;   generating a representative set of content items associated with the user-defined hash-tag, wherein the representative set of content items comprises a plurality of content items;   determining, via the review system and from the representative set of content items, a first plurality of content items that include the user-defined hash-tag and have top numbers of user engagements;   determining, via the review system and from the representative set of content items, a second plurality of content items that include the user-defined hash-tag and were posted most recently; and   providing the first plurality of content items and the second plurality of content items together via a review graphical user interface.   
     
     
         11 . The computer-readable medium of  claim 10 , wherein the operations further comprise:
 generating, based on the manual review of the representative set of content items associated with the user-defined hash-tag via the review graphical user interface, one or more manual review metrics;   analyzing media moderation associated with the user-defined hash-tag to determine a moderated media metric associated with the user-defined hash-tag; and   utilizing the one or more manual review metrics and the moderated media metric to customize a set of restrictions for the user-defined hash-tag.   
     
     
         12 . The computer-readable medium of  claim 11 , wherein utilizing the one or more manual review metrics and the moderated media metric to customize the set of restrictions for the user-defined hash-tag comprises comparing the one or more manual review metrics to one or more manual review thresholds and comparing the moderated media metric to a moderated media threshold. 
     
     
         13 . The computer-readable medium of  claim 11 , wherein generating the one or more manual review metrics comprises utilizing the representative set of content items to generate at least one of a violation percentage for top media associated with the user-defined hash-tag, a violation percentage for recent media associated with the user-defined hash-tag, or an overall violation percentage for media associated with the user-defined hash-tag. 
     
     
         14 . The computer-readable medium of  claim 11 , wherein the operations further comprise generating, for the user-defined hash-tag, one of a positive classification, a neutral classification, and a negative classification. 
     
     
         15 . The computer-readable medium of  claim 11 , wherein analyzing the media moderation comprises determining a percent of media comprising the user-defined hash-tag deleted for violating one or more guidelines, terms, and/or conditions of a social networking system. 
     
     
         16 . A system comprising:
 at least one computer-readable storage device; and   at least one processor coupled to the at least one computer-readable storage device, the at least one processor configured to cause the system to:
 trigger a manual review of media associated with a user-defined hash-tag via a review system; 
 generate a representative set of content items associated with the user-defined hash-tag, wherein the representative set of content items comprises a plurality of content items; 
 determine, via the review system and from the representative set of content items, a first plurality of content items that include the user-defined hash-tag and have top numbers of user engagements; 
 determine, via the review system and from the representative set of content items, a second plurality of content items that include the user-defined hash-tag and were posted most recently; and 
 provide the first plurality of content items and the second plurality of content items together via a review graphical user interface. 
   
     
     
         17 . The system of  claim 16 , wherein the at least one processor is further configured to cause the system to:
 generate, based on the manual review of the representative set of content items associated with the user-defined hash-tag via the review graphical user interface, one or more manual review metrics;   analyze media moderation associated with the user-defined hash-tag to determine a moderated media metric associated with the user-defined hash-tag; and   utilize the one or more manual review metrics and the moderated media metric to customize a set of restrictions for the user-defined hash-tag.   
     
     
         18 . The system of  claim 17 , wherein the at least one processor is further configured to cause the system to generate the one or more manual review metrics by utilizing the representative set of content items to generate at least one of a violation percentage for top media associated with the user-defined hash-tag, a violation percentage for recent media associated with the user-defined hash-tag, or an overall violation percentage for media associated with the user-defined hash-tag. 
     
     
         19 . The system of  claim 17 , wherein the at least one processor is further configured to cause the system to analyze the media moderation by determining a percent of media comprising the user-defined hash-tag deleted for violating one or more guidelines, terms, or conditions of a social networking system. 
     
     
         20 . The system of  claim 16 , further comprising instructions that, when executed by the at least one processor, cause the system to generate, for the user-defined hash-tag, a positive classification, a neutral classification, or a negative classification.