Abstract: A method disclosed herein provides for escalation of machine learning content selection for content moderation use. The method includes requesting reaction feedback from users of an online social community platform in association with each of a number of user-provided content items appearing in the online social community platform. The reaction feedback is analyzed to identify a subset of the user-provided content items satisfying reaction consensus criteria, and content moderation logic is then trained based on the subset of content items identified from the analysis of the reaction feedback to facilitate selective implementation of content moderation actions based on the trained content moderation logic.

Abstract: Embodiments are disclosed that relate to enforcement of user policies in a multi-user interactive computing environment by end user review. For example, one disclosed embodiment provides, on a computing device, a method comprising receiving a notification of a current policy controversy, and sending information regarding the current policy controversy to each end user reviewer of a plurality of end user reviewers, each end user reviewer being a member of an enforcement federation of a plurality of enforcement federations. The method further comprises receiving enforcement decisions from one or more responding end user reviewers of the plurality of end user reviewers, and if the enforcement decisions received meet an enforcement threshold, then automatically enforcing a policy rule.

Abstract: Embodiments are disclosed that relate to enforcement of user policies in a multi-user interactive computing environment by end user review. For example, one disclosed embodiment provides, on a computing device, a method comprising receiving a notification of a current policy controversy, and sending information regarding the current policy controversy to each end user reviewer of a plurality of end user reviewers, each end user reviewer being a member of an enforcement federation of a plurality of enforcement federations. The method further comprises receiving enforcement decisions from one or more responding end user reviewers of the plurality of end user reviewers, and if the enforcement decisions received meet an enforcement threshold, then automatically enforcing a policy rule.

Abstract: Embodiments are disclosed that relate to enforcement of user policies in a multi-user interactive computing environment by end user review. For example, one disclosed embodiment provides, on a computing device, a method comprising receiving a notification of a current policy controversy, and sending information regarding the current policy controversy to each end user reviewer of a plurality of end user reviewers, each end user reviewer being a member of an enforcement federation of a plurality of enforcement federations. The method further comprises receiving enforcement decisions from one or more responding end user reviewers of the plurality of end user reviewers, and if the enforcement decisions received meet an enforcement threshold, then automatically enforcing a policy rule.

Abstract: Embodiments are disclosed that relate to enforcement of user policies in a multi-user interactive computing environment by end user review. For example, one disclosed embodiment provides, on a computing device, a method comprising receiving a notification of a current policy controversy, and sending information regarding the current policy controversy to each end user reviewer of a plurality of end user reviewers, each end user reviewer being a member of an enforcement federation of a plurality of enforcement federations. The method further comprises receiving enforcement decisions from one or more responding end user reviewers of the plurality of end user reviewers, and if the enforcement decisions received meet an enforcement threshold, then automatically enforcing a policy rule.