Microsoft Technology Licensing, LLC

Arnav Kumar Agrawal

Robert Mitchell Smith

Alexis Descre

William Sean Sheehan

Donald T Sprague

Kristopher Makey

Warren Alpert

Warren Michael Alpert

Kristopher Aaron Makey

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.

Adverse user behavior detection and mitigation

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Bellevue, WA, United States of America

Arnav Kumar Agrawal