Manipulating Elections by Changing Voter Perceptions

TL;DR

This paper models how manipulating voter perceptions affects election outcomes using spatial voting theory, revealing computational complexity and conditions under which control is feasible.

Contribution

It introduces a formal model of perception manipulation in elections and analyzes its computational complexity, highlighting the impact of voter opinion diversity.

Findings

Controlling elections is NP-hard with diverse opinions.

When opinions are polarized, control becomes polynomial-time solvable.

The model applies to both binary and real-valued issue spaces.

Abstract

The integrity of elections is central to democratic systems. However, a myriad of malicious actors aspire to influence election outcomes for financial or political benefit. A common means to such ends is by manipulating perceptions of the voting public about select candidates, for example, through misinformation. We present a formal model of the impact of perception manipulation on election outcomes in the framework of spatial voting theory, in which the preferences of voters over candidates are generated based on their relative distance in the space of issues. We show that controlling elections in this model is, in general, NP-hard, whether issues are binary or real-valued. However, we demonstrate that critical to intractability is the diversity of opinions on issues exhibited by the voting public. When voter views lack diversity, and we can instead group them into a small number of categories -- for example, as a result of political polarization -- the election control problem can be solved in polynomial time in the number of issues and candidates for arbitrary scoring rules.