SOTAVerified

Adversarial Learning for Zero-Shot Stance Detection on Social Media

2021-05-14NAACL 2021Code Available1· sign in to hype

Emily Allaway, Malavika Srikanth, Kathleen McKeown

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

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.

Tasks

Reproductions