Representative Ranking for Deliberation in the Public Sphere
March 19, 2025 Β· Declared Dead Β· π International Conference on Machine Learning
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Authors
Manon Revel, Smitha Milli, Tyler Lu, Jamelle Watson-Daniels, Max Nickel
arXiv ID
2503.18962
Category
cs.SI: Social & Info Networks
Cross-listed
cs.LG
Citations
4
Venue
International Conference on Machine Learning
Last Checked
4 months ago
Abstract
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.
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