Fighting Abuse @Scale 2019 recap

What this post added

This post details technical approaches to fighting abuse at scale, including deep entity classification (DEC) using multi-stage, multi-task learning and social graph embeddings to detect fake accounts; unsupervised learning for detecting fake/compromised accounts and abusive automation; temporal interaction embeddings (TIEs) to capture user behavior sequences for integrity issue detection; and collaborative efforts between sharing and hosting platforms to identify and remove terrorist content. It also covers building and scaling human review systems for content labeling and enforcement, and detecting payment and revenue share fraud using machine learning and heuristic-based algorithms.