Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
110 tokens/sec
GPT-4o
56 tokens/sec
Gemini 2.5 Pro Pro
44 tokens/sec
o3 Pro
6 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Election Control by Manipulating Issue Significance (2007.09786v1)

Published 19 Jul 2020 in cs.GT and cs.MA

Abstract: 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. One means of election control that has been proposed 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 is 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 enables tractable manipulation.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (4)
  1. Andrew Estornell (14 papers)
  2. Sanmay Das (19 papers)
  3. Edith Elkind (78 papers)
  4. Yevgeniy Vorobeychik (124 papers)
Citations (3)

Summary

We haven't generated a summary for this paper yet.