Adverse User Behavior Detection and Mitigation

• Main Authors: ALPERT, Warren Michael, SHEEHAN, William Sean, AGRAWAL, Arnav Kumar, SPRAGUE, Donald T, DESCRE, Alexis, SMITH, Robert Mitchell, MAKEY, Kristopher Aaron
• Format: Patent
• Language: English
• Published: 05.05.2022
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

Aspects of the present disclosure relate to adverse user behavior detection and mitigation. In examples, a user account of a social platform may be trusted or untrusted. If the user account is untrusted, activity of the user account may be buffered so as to not directly affect social metrics of the social platform. For example, if the untrusted user account follows a target user account, the untrusted user account may be added to a separate set of followers or otherwise separated from a set of trusted followers of the target user account. Eventually, each user account in the separate set is evaluated to determine whether the user account has transitioned to a trusted user. If the user account is now trusted, it may be migrated to the set of trusted followers. However, if the user account is untrusted, it may be removed from the separate set, thereby reverting the activity.