On the Robustness of Democratic Electoral Processes to Computational Propaganda

TL;DR

This paper develops a mathematical model to analyze how different social and electoral system characteristics influence the resilience of democratic elections against digital misinformation campaigns.

Contribution

It introduces a novel electoral model to evaluate the impact of voter bias, polarization, and electoral system design on election robustness against manipulation.

Findings

Biased electorates with clear outcomes are more resilient.

Less polarized and highly interactive electorates are more resistant to manipulation.

Proportional representation systems are generally more robust.

Abstract

There is growing evidence of systematic attempts to influence democratic elections by controlled and digitally organized dissemination of fake news. This raises the question of the intrinsic robustness of democratic electoral processes against external influences. Particularly interesting is to identify the social characteristics of a voter population that renders it more resilient against opinion manipulation. Equally important is to determine which of the existing democratic electoral systems is more robust to external influences. Here we construct a mathematical electoral model to address these two questions. We find that, not unexpectedly, biased electorates with clear-cut elections are overall quite resilient against opinion manipulations, because inverting the election outcome requires to change the opinion of many voters. More interesting are unbiased or weakly biased electorates with close elections. We find that such populations are more resilient against opinion manipulations (i) if they are less polarized and (ii) when voters interact more with each other, regardless of their opinion differences, and that (iii) electoral systems based on proportional representation are generally the most robust. Our model qualitatively captures the volatility of the US House of Representatives elections. We take this as a solid validation of our approach.