# A Note on Data Simulations for Voting by Evaluation

arXiv: https://arxiv.org/abs/2104.07666 · HTML: https://mlsanity.com/paper/2104.07666/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 28 references that are in the map.
- First posted on arXiv 15 Apr 2021.

## Built on by (most cited first, 1 of 1)

- [Learning Resilient Elections with Adversarial GNNs](https://mlsanity.com/paper/2601.01653/) (2026)

## Abstract (arXiv)

Voting rules based on evaluation inputs rather than preference orders have been recently proposed, like majority judgement, range voting or approval voting. Traditionally, probabilistic analysis of voting rules supposes the use of simulation models to generate preferences data, like the Impartial Culture (IC) or Impartial and Anonymous Culture (IAC) models. But these simulation models are not suitable for the analysis of evaluation-based voting rules as they generate preference orders instead of the needed evaluations. We propose in this paper several simulation models for generating evaluation-based voting inputs. These models, inspired by classical ones, are defined, tested and compared for recommendation purpose.