Selecting Interlacing Committees

2025-09-02

AI Summary

This paper addresses societal polarization by introducing *social connectedness*—a novel concept—into the computational social choice framework of committee elections. To mitigate group fragmentation exacerbated by representative institutions, we define two computationally tractable measures of committee connectedness and systematically characterize their approximation trade-offs with excellence, diversity, and proportional representation. Under the setting where voters and candidates exhibit interval preferences, we design polynomial-time optimal algorithms for single-objective connectedness optimization. Furthermore, we propose the first multi-objective algorithm with constant-factor approximation guarantees, simultaneously approximating connectedness, representativeness, and diversity. Theoretical analysis and algorithmic implementation jointly demonstrate that efficient and balanced committee selection is feasible under structured preference domains.

Technology Category

Knowledge Representation and Reasoning: PreferencesGame Theory and Economic Paradigms: Social Choice / VotingConstraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarizationEconomics, Online Markets and Human Computation: Fairness, privacy, and diversity in economic environmentsGraph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs

Abstract

Polarization is a major concern for a well-functioning society. Often, mass polarization of a society is driven by polarizing political representation, even when the latter is easily preventable. The existing computational social choice methods for the task of committee selection are not designed to address this issue. We enrich the standard approach to committee selection by defining two quantitative measures that evaluate how well a given committee interconnects the voters. Maximizing these measures aims at avoiding polarizing committees. While the corresponding maximization problems are NP-complete in general, we obtain efficient algorithms for profiles in the voter-candidate interval domain. Moreover, we analyze the compatibility of our goals with other representation objectives, such as excellence, diversity, and proportionality. We identify trade-offs between approximation guarantees, and describe algorithms that achieve simultaneous constant-factor approximations.

Problem

• Addressing societal polarization through committee selection methods
• Evaluating committee interconnectedness to avoid polarizing representation
• Balancing interconnection with excellence, diversity, and proportionality objectives

Innovation

• Interlacing committees to reduce polarization
• Efficient algorithms for voter-candidate interval domains
• Constant-factor approximations for multiple representation objectives