Diversity, Agreement, and Polarization in Elections
Abstract
We consider the notions of agreement, diversity, and polarization in ordinal elections (that is, in elections where voters rank the candidates). While (computational) social choice offers good measures of agreement between the voters, such measures for the other two notions are lacking. We attempt to rectify this issue by designing appropriate measures, providing means of their (approximate) computation, and arguing that they, indeed, capture diversity and polarization well. In particular, we present "maps of preference orders" that highlight relations between the votes in a given election and which help in making arguments about their nature.
Cite
Text
Faliszewski et al. "Diversity, Agreement, and Polarization in Elections." International Joint Conference on Artificial Intelligence, 2023. doi:10.24963/IJCAI.2023/299Markdown
[Faliszewski et al. "Diversity, Agreement, and Polarization in Elections." International Joint Conference on Artificial Intelligence, 2023.](https://mlanthology.org/ijcai/2023/faliszewski2023ijcai-diversity/) doi:10.24963/IJCAI.2023/299BibTeX
@inproceedings{faliszewski2023ijcai-diversity,
title = {{Diversity, Agreement, and Polarization in Elections}},
author = {Faliszewski, Piotr and Kaczmarczyk, Andrzej and Sornat, Krzysztof and Szufa, Stanislaw and Was, Tomasz},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2023},
pages = {2684-2692},
doi = {10.24963/IJCAI.2023/299},
url = {https://mlanthology.org/ijcai/2023/faliszewski2023ijcai-diversity/}
}