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Representative Ranking for Deliberation in the Public Sphere

ICML 2025 · Label-efficient and robust learning › Recognition and long-tail · approach: Recommendation representation learning

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Introduces justified representation (JR) as a constraint on comment ranking so that platform-optimized sets (engagement, diverse approval, Perspective API bridging scores) still represent all large cohesive user groups, proving low price of JR under clustered preferences and validating with GreedyCC on Remesh campus-protest data.

Problem

Algorithmic comment ranking that optimizes civility or bridging or engagement can suppress legitimate viewpoints; deliberation requires representation of diverse views, which existing ranking methods do not guarantee.

Approach

Adds the social-choice axiom of justified representation as a hard constraint on the top-k comment set, maximizing any score function subject to JR, and analyzes the price of JR across score-function classes and under Mallows mixture preference models.

Key results

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Enforce JR with GreedyCCEngagement ranking · Remesh campus protest discussions, 10 questionsunrepresented users: 18% -> 5%Helped
Enforce JR with GreedyCCMaximin diverse approval ranking · Remesh campus protest discussions, 10 questionsunrepresented users: 15% -> 4%Helped
Enforce JR with GreedyCCPerspective API ranking · Remesh campus protest discussions, 10 questionsunrepresented users: 4% -> 2%Helped
Enforce JR with GreedyCCEngagement ranking · Remesh campus protest discussions, 10 questionsengagement score: 1.05Hurt
Enforce JR with GreedyCCMaximin diverse approval ranking · Remesh campus protest discussions, 10 questionsmaximin diverse approval score: 1.06Hurt
Enforce JR with GreedyCCPerspective API ranking · Remesh campus protest discussions, 10 questionsPerspective API bridging score: 1.18Hurt
Use GreedyCC to enforce JRComment ranking across scoring functions · Remesh campus protest discussionsrepresentation of political groups: 100%, 100%, and 70%Helped

Surprising findings

Limitations

Experimental setup

Datasets: Remesh campus protests dataset (approx. 300 participants per session, two sessions, ten questions)

Benchmarks: Remesh campus protests dataset

Metrics: user representation rate JR satisfaction rate price of GreedyCC diverse approval engagement Perspective API bridging score

Baselines: engagement ranking maximin diverse approval ranking Perspective API bridging ranking

Builds on: justified representation (Aziz et al.) GreedyCC Mallows model Perspective API

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