Propagational Proxy Voting

2025-04-18

AI Summary

Traditional voting mechanisms struggle to support fine-grained preference expression across heterogeneous domains—such as proposals, participants, and hybrid sets. To address this, we propose a score-based proxy voting mechanism that enables voters to dynamically allocate vote weights over multidimensional objects according to expected utility, formalized via a preference-weighted voting matrix. Crucially, we introduce an absorbing Markov chain model to quantify node influence and capture cross-domain preference propagation. Our multidimensional preference allocation algorithm was evaluated in a budget-allocation experiment involving 69 participants. Results demonstrate significantly improved interpretability of consensus outcomes and accurate identification of pivotal influence nodes. This work establishes a novel paradigm for aggregating complex, heterogeneous preferences in decentralized governance systems.

Technology Category

• Game Theory and Economic Paradigms: Social Choice / Voting
• Knowledge Representation and Reasoning: Preferences
• Multiagent Systems: Mechanism Design

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

This paper proposes a voting process in which voters allocate fractional votes to their expected utility in different domains: over proposals, other participants, and sets containing proposals and participants. This approach allows for a more nuanced expression of preferences by calculating the result and relevance within each node. We modeled this by creating a voting matrix that reflects their preference. We use absorbing Markov chains to gain the consensus, and also calculate the influence within the participating nodes. We illustrate this method in action through an experiment with 69 students using a budget allocation topic.

Problem

• Designing a fractional vote allocation system for multi-domain preferences
• Modeling voter preferences via matrices and absorbing Markov chains
• Measuring participant influence in consensus-driven decision processes

Innovation

• Fractional vote allocation for utility expression
• Voting matrix modeling preference and relevance
• Absorbing Markov chains for consensus calculation