Adversarial Learning for Zero-Shot Stance Detection on Social Media

Understand

Stance detection on social media can help to identify and understand slanted news or commentary in everyday life.

• In this work, we propose a new model for zero-shot stance detection on Twitter that uses adversarial learning to generalize across topics.
• Our model achieves state-of-the-art performance on a number of unseen test topics with minimal computational costs.
• In addition, we extend zero-shot stance detection to new topics, highlighting future directions for zero-shot transfer.