Measuring and Controlling Divisiveness in Rank Aggregation

Rachael Colley; Umberto Grandi; César Hidalgo; Mariana Macedo; Carlos Navarrete

IJCAI 2023poster7 citations

Measuring and Controlling Divisiveness in Rank Aggregation

Rachael Colley, Umberto Grandi, César Hidalgo, Mariana Macedo, Carlos Navarrete

Abstract

In rank aggregation, members of a population rank issues to decide which are collectively preferred. We focus instead on identifying divisive issues that express disagreements among the preferences of individuals. We analyse the properties of our divisiveness measures and their relation to existing notions of polarisation. We also study their robustness under incomplete preferences and algorithms for control and manipulation of divisiveness. Our results advance our understanding of how to quantify disagreements in collective decision-making.

Game Theory and Economic Paradigms: GTEP: Computational social choiceKnowledge Representation and Reasoning: KRR: Preference modelling and preference-based reasoningMultidisciplinary Topics and Applications: MDA: Social sciences

BibTeX

@inproceedings{ijcai2023p291,
  title     = {Measuring and Controlling Divisiveness in Rank Aggregation},
  author    = {Colley, Rachael and Grandi, Umberto and Hidalgo, César and Macedo, Mariana and Navarrete, Carlos},
  booktitle = {Proceedings of the Thirty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-23}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Edith Elkind},
  pages     = {2616--2623},
  year      = {2023},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2023/291},
  url       = {https://doi.org/10.24963/ijcai.2023/291},
}