Critical noise can make the minority candidate win: The US Presidential Election cases

TL;DR

This paper models how coarse-grained voting systems like the US Electoral College can lead to minority candidates winning elections due to critical noise effects, especially near phase transition points.

Contribution

It introduces a model linking opinion dynamics and coarse graining to explain minority wins, highlighting the impact of critical fluctuations in electoral systems.

Findings

Minority candidates can win due to critical noise effects.

Coarse graining increases the probability of minority wins.

Predictions suggest more minority wins in future elections.

Abstract

A national voting population, when segmented into groups like, for example, different states, can yield a counter-intuitive scenario where the winner may not necessarily get the most number of total votes. A recent example is the 2016 presidential election in the US. We model the situation by using interacting opinion dynamics models and look at the effect of coarse graining near the critical points where the spatial fluctuations are high. We establish that the sole effect of coarse graining, which mimics the `winner takes all' electoral college system in the US, can give rise to finite probabilities of such events of minority candidate winning even in the large size limit near the critical point. The overall probabilities of victory of the minority candidate can be predicted from the models which indicates that one may expect more instances of minority candidate winning in the future.

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