Representative Ranking for Deliberation in the Public Sphere
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866918086688374784 |
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| author | Revel, Manon Milli, Smitha Lu, Tyler Watson-Daniels, Jamelle Nickel, Max |
| author_facet | Revel, Manon Milli, Smitha Lu, Tyler Watson-Daniels, Jamelle Nickel, Max |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_18962 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Representative Ranking for Deliberation in the Public Sphere Revel, Manon Milli, Smitha Lu, Tyler Watson-Daniels, Jamelle Nickel, Max Social and Information Networks Machine Learning 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. |
| title | Representative Ranking for Deliberation in the Public Sphere |
| topic | Social and Information Networks Machine Learning |
| url | https://arxiv.org/abs/2503.18962 |