Detecting Fake News With Weak Social Supervision

Limited labeled data are becoming one of the largest bottlenecks for supervised learning systems. This is especially the case for many real-world tasks, where large-scale labeled examples are either too expensive to acquire or unavailable due to privacy or data access constraints. Weak supervision has shown to be effective in mitigating the scarcity of labeled data by leveraging weak labels or inj...