# Understanding Distance Measures Among Elections

arXiv: https://arxiv.org/abs/2205.00492 · HTML: https://mlsanity.com/paper/2205.00492/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 May 2022.

## Built on by (most cited first, 5 of 5)

- [Expected Frequency Matrices of Elections: Computation, Geometry, and Preference Learning](https://mlsanity.com/paper/2205.07831/) (2022)
- [Drawing a Map of Elections](https://mlsanity.com/paper/2504.03809/) (2025)
- [Diversity of Structured Domains via k-Kemeny Scores](https://mlsanity.com/paper/2509.15812/) (2025)
- [A Map of Diverse Synthetic Stable Roommates Instances](https://mlsanity.com/paper/2208.04041/) (2022)
- [Eliciting Kemeny Rankings](https://mlsanity.com/paper/2312.11663/) (2023)

## Abstract (arXiv)

Motivated by putting empirical work based on (synthetic) election data on a more solid mathematical basis, we analyze six distances among elections, including, e.g., the challenging-to-compute but very precise swap distance and the distance used to form the so-called map of elections. Among the six, the latter seems to strike the best balance between its computational complexity and expressiveness.