Abstract: Toxicity-shield modules are activated with respect to participants of a multiuser virtual environment to shield individual participants from toxic behaviors. The toxicity-shield modules may be customized for each participant of the multiuser virtual environment based on tolerances of each participant for exposure to predetermined toxic behavior(s). The toxicity-shield modules may be activated during the multiuser virtual environment to monitor communications data (e.g., voice-based and/or text-based “chats” and/or a video stream) between the participants and to manage the exposure level of individual participants to the predetermined toxic behavior(s).

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.