Papers › Adversarial Learning for Zero-Shot Stance Detection on Social Media
Adversarial Learning for Zero-Shot Stance Detection on Social Media
Emily Allaway, Malavika Srikanth, Kathleen McKeown
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.
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