Promoting Constructive Deliberation: Reframing for Receptiveness

TL;DR

This paper introduces a computational framework for automatically reframing online responses to controversial comments, enhancing perceived receptiveness and promoting constructive deliberation through six identified strategies.

Contribution

It presents a novel, psychology-informed approach to automatically reframe responses, improving perceived receptiveness in online discussions using a new dataset and human-centered evaluation.

Findings

Reframed replies are perceived as more receptive than original responses.

The framework significantly outperforms generic baselines in human evaluations.

Transforming social science constructs into computational models can improve language model alignment.

Abstract

To promote constructive discussion of controversial topics online, we propose automatic reframing of disagreeing responses to signal receptiveness to a preceding comment. Drawing on research from psychology, communications, and linguistics, we identify six strategies for reframing. We automatically reframe replies to comments according to each strategy, using a Reddit dataset. Through human-centered experiments, we find that the replies generated with our framework are perceived to be significantly more receptive than the original replies and a generic receptiveness baseline. We illustrate how transforming receptiveness, a particular social science construct, into a computational framework, can make LLM generations more aligned with human perceptions. We analyze and discuss the implications of our results, and highlight how a tool based on our framework might be used for more teachable and creative content moderation.