A networked voting rule for democratic representation

TL;DR

This paper proposes a networked voting framework for democratic representation that enhances accountability and scalability, outperforming traditional methods in simulations, and reveals a mathematical relation between committee size and population.

Contribution

It introduces a novel decentralized voting algorithm, analyzes its scalability, and demonstrates its effectiveness through simulations across various network structures.

Findings

High representativeness with small committees

Inverse square root law relating committee size and population

Scalability to large populations with minimal network influence

Abstract

We introduce a general framework for exploring the problem of selecting a committee of representatives with the aim of studying a networked voting rule based on a decentralized large-scale platform, which can assure a strong accountability of the elected. The results of our simulations suggest that this algorithm-based approach is able to obtain a high representativeness for relatively small committees, performing even better than a classical voting rule based on a closed list of candidates. We show that a general relation between committee size and representatives exists in the form of an inverse square root law and that the normalized committee size approximately scales with the inverse of the community size, allowing the scalability to very large populations. These findings are not strongly influenced by the different networks used to describe the individuals interactions, except for the presence of few individuals with very high connectivity which can have a marginally negative effect in the committee selection process.