# Collecting, Classifying, Analyzing, and Using Real-World Elections

arXiv: https://arxiv.org/abs/2204.03589 · HTML: https://mlsanity.com/paper/2204.03589/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Apr 2022.

## Built on by (most cited first, 3 of 3)

- [Expected Frequency Matrices of Elections: Computation, Geometry, and Preference Learning](https://mlsanity.com/paper/2205.07831/) (2022)
- [A Map of Diverse Synthetic Stable Roommates Instances](https://mlsanity.com/paper/2208.04041/) (2022)
- [Soft Tournament Equilibrium: Differentiable Set-Valued Inference for Non-Transitive Pairwise Comparisons](https://mlsanity.com/paper/2604.04328/) (2026)

## Abstract (arXiv)

We present a collection of 7582 real-world elections divided into 25 datasets from various sources ranging from sports competitions over music charts to survey- and indicator-based rankings. We provide evidence that the collected elections complement already publicly available data from the PrefLib database, which is currently the biggest and most prominent source containing 701 real-world elections from 36 datasets. Using the map of elections framework, we divide the datasets into three categories and conduct an analysis of the nature of our elections. To evaluate the practical applicability of previous theoretical research on (parameterized) algorithms and to gain further insights into the collected elections, we analyze different structural properties of our elections including the level of agreement between voters and election's distances from restricted domains such as single-peakedness. Lastly, we use our diverse set of collected elections to shed some further light on several traditional questions from social choice, for instance, on the number of occurrences of the Condorcet paradox and on the consensus among different voting rules.