Description
"Election Control by Manipulating Issue Significance
Andrew Estornell (Washington University in St Louis)*; Sanmay Das (Washington University in St. Louis); Edith Elkind (Oxford University); Yevgeniy Vorobeychik (Washington University in St. Louis)
Integrity of elections is vital to democratic systems, but it is frequently threatened by malicious actors. The study of algorithmic complexity of the problem of manipulating election outcomes by changing its structural features is known as election control Rothe [2016]. One means of election control that has been proposed, pertinent to the spatial voting model, is to select a subset of issues that determine voter preferences over candidates. We study a variation of this model in which voters have judgments about relative importance of issues, and a malicious actor can manipulate these judgments. We show that computing effective manipulations in this model is NP-hard even with two candidates or binary issues. However, we demonstrate that the problem becomes tractable with a constant number of voters or issues. Additionally, while it remains intractable when voters can vote stochastically, we exhibit an important special case in which stochastic voting behavior enables tractable manipulation."