Representative Ranking for Deliberation in the Public Sphere

Online comment sections, such as those on news sites or social media, have the potential to foster informal public deliberation, However, this potential is often undermined by the frequency of toxic or low-quality exchanges that occur in these settings. To combat this, platforms increasingly leverage algorithmic ranking to facilitate higher-quality discussions, e.g., by using civility classifiers or forms of prosocial ranking. Yet, these interventions may also inadvertently reduce the visibility of legitimate viewpoints, undermining another key aspect of deliberation: representation of diverse views. We seek to remedy this problem by introducing guarantees of representation into these methods. In particular, we adopt the notion of justified representation (JR) from the social choice literature and incorporate a JR constraint into the comment ranking setting. We find that enforcing JR leads to greater inclusion of diverse viewpoints while still being compatible with optimizing for user engagement or other measures of conversational quality.

Online comment sections on news sites and social media can encourage public discussions, but they often suffer from toxic or low-quality interactions. To improve the quality of these discussions, algorithms are used to rank comments, focusing on civility and positive interactions. However, these methods can unintentionally limit the diversity of opinions represented. To address this, we propose a new approach that ensures diverse viewpoints are included by using a concept from social choice theory called justified representation (JR). By applying JR to comment ranking, our research shows that it significantly enhances the representation and inclusivity of different views without negatively affecting the quality of conversations or user engagement.