Putting a Compass on the mAP of Elections
Abstract
In their AAMAS 2020 paper, Szufa et al. presented a "map of elections" that visualizes a set of 800 elections generated from various statistical cultures. While similar elections are grouped together on this map, there is no obvious interpretation of the elections' positions. We provide such an interpretation by introducing four canonical “extreme” elections, acting as a compass on the map. We use them to analyze both a dataset provided by Szufa et al. and a number of real-life elections. In effect, we find a new parameterization of the Mallows model, based on measuring the expected swap distance from the central preference order, and show that it is useful for capturing real-life scenarios.
Cite
Text
Boehmer et al. "Putting a Compass on the mAP of Elections." International Joint Conference on Artificial Intelligence, 2021. doi:10.24963/IJCAI.2021/9Markdown
[Boehmer et al. "Putting a Compass on the mAP of Elections." International Joint Conference on Artificial Intelligence, 2021.](https://mlanthology.org/ijcai/2021/boehmer2021ijcai-putting/) doi:10.24963/IJCAI.2021/9BibTeX
@inproceedings{boehmer2021ijcai-putting,
title = {{Putting a Compass on the mAP of Elections}},
author = {Boehmer, Niclas and Bredereck, Robert and Faliszewski, Piotr and Niedermeier, Rolf and Szufa, Stanislaw},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2021},
pages = {59-65},
doi = {10.24963/IJCAI.2021/9},
url = {https://mlanthology.org/ijcai/2021/boehmer2021ijcai-putting/}
}