Gerrymandering over graphs

Amittai Cohen-Zemach, Yoad Lewenberg, Jeffrey S. Rosenschein

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

17 Scopus citations

Abstract

In many real-life scenarios, voting problems consist of several phases: an overall set of voters is partitioned into subgroups, each subgroup chooses a preferred candidate, and the final winner is selected from among those candidates. The attempt to skew the outc ome of such a voting system through strategic partitioning of the overall set of voters into subgroups is known as "gerrymandering". We investigate the problem of gerrymandering over a network structure; the voters are embedded in a social network, and the task is to divide the network into connected components such that a target candidate wiU win in a plurality of the components. We first show that the problem is NP-complete in the worst case. We then perform a series of simulations, using random graph models incorporating a homophily factor. In these simulations, we show that a simple greedy algorithm can be quite successful in finding a partition in favor of a specific candidate.

Original languageAmerican English
Title of host publication17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages274-282
Number of pages9
ISBN (Print)9781510868083
StatePublished - 2018
Event17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018 - Stockholm, Sweden
Duration: 10 Jul 201815 Jul 2018

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume1
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
Country/TerritorySweden
CityStockholm
Period10/07/1815/07/18

Bibliographical note

Publisher Copyright:
© 2018 International Foundation for Autonomous Agents and Multiagent Systems.

Keywords

  • Districts
  • Gerrymandering
  • Social Choice
  • Social Networks
  • Voting

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