DEC learns to differentiate fake and real users by their connection patterns across the network. It calls these “deep features,” and they include things like the average age or gender distribution of the user’s friends. Facebook uses over 20,000 deep features to characterize each account, providing a snapshot of how each profile behaves to make it difficult for attackers to game the system by changing tactics.
The system starts by using a large number of low-precision machine-generated labels. These are generated through a mix of rules and other machine-learning models that estimate whether users are real or fake. Once that data is used to train a neural network, the model is then fine-tuned with a small batch of high-precision hand-labeled data, generated by people around the world who have an understanding of local cultural norms.
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