Inducing Positive Perspectives with Text Reframing
Caleb Ziems, Minzhi Li, Anthony Lin Zhang, Diyi Yang · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · 2022
Sentiment transfer is one popular example of a text style transfer task, where the goal is to reverse the sentiment polarity of a text.With a sentiment reversal comes also a reversal in meaning.We introduce a different but related task called positive reframing in which we neutralize a negative point of view and generate a more positive perspective for the author without contradicting the original meaning.Our insistence on meaning preservation makes positive reframing a challenging and semantically rich task.To facilitate rapid progress, we introduce a large-scale benchmark, POSITIVE PSY-CHOLOGY FRAMES, with 8,349 sentence pairs and 12,755 structured annotations to explain positive reframing in terms of six theoreticallymotivated reframing strategies.Then we evaluate a set of state-of-the-art text style transfer models, and conclude by discussing key challenges and directions for future work.To download the data, see https://github. com/GT-SALT/positive-frames