Proceedings

Agreement, Diversity, and Polarization Indices for Approval Elections

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Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Main Track. Pages 3393-3401.

https://doi.org/10.24963/ijcai.2026/377

Abstract

An index is a function that measures the extent to which an election has a particular feature. We seek indices that capture agreement, diversity, and polarization among voters in approval elections, normalized with respect to saturation. The latter means that if two elections differ by the fraction of candidates approved by an average voter, but otherwise are of similar nature, then they should have similar index values. We propose several indices, analyze their properties, and use them to derive a new map of approval elections, and compare various real-life elections from Pabulib, Preflib and other sources.

Piotr Faliszewski, Jitka Mertlová, Krzysztof Sornat, Stanisław Szufa, and Tomasz Wąs. 2026. Agreement, Diversity, and Polarization Indices for Approval Elections. In Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26. IJCAI, 3393–3401. https://doi.org/10.24963/ijcai.2026/377
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