QUEST: Queue Simulation for Content Moderation at Scale

TL;DR

This paper presents a queue simulation approach to optimize large-scale social media content moderation systems, combining operations research techniques with machine learning and manual review processes.

Contribution

It introduces a novel application of queueing theory and simulation to improve the efficiency of large-scale content moderation systems.

Findings

Effective modeling of moderation workflows

Insights into system capacity and bottlenecks

Guidelines for scaling manual review processes

Abstract

Moderating content in social media platforms is a formidable challenge due to the unprecedented scale of such systems, which typically handle billions of posts per day. Some of the largest platforms such as Facebook blend machine learning with manual review of platform content by thousands of reviewers. Operating a large-scale human review system poses interesting and challenging methodological questions that can be addressed with operations research techniques. We investigate the problem of optimally operating such a review system at scale using ideas from queueing theory and simulation.