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09-07-2024 | Original Paper

Probabilistic models of profiles for voting by evaluation

Authors: Antoine Rolland, Jean-Baptiste Aubin, Irène Gannaz, Samuela Leoni

Published in: Social Choice and Welfare | Issue 2/2024

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Abstract

The article introduces probabilistic models for evaluation-based voting, contrasting with traditional ranking-based methods. It discusses the properties of voting rules, focusing on the probabilistic approach to determine the likelihood of certain properties. The text covers various generative models for both continuous and discrete evaluations, including Uniform, Beta, and spatial models. It also highlights the use of copulas to model dependencies between evaluations and provides real-world examples of fitting these models to observed data. The article concludes by emphasizing the importance of these models for simulating realistic voting scenarios and understanding the underlying preferences of voters.

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Data are available in the supplementary material. The association is the Eclaireuses and Eclaireurs Unionistes de France and the general assembly stood in January 2022 in Bordeaux, France. Data are from private communication.

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Title: Probabilistic models of profiles for voting by evaluation
Authors: Antoine Rolland
Jean-Baptiste Aubin
Irène Gannaz
Samuela Leoni
Publication date: 09-07-2024
Publisher: Springer Berlin Heidelberg
Published in: Social Choice and Welfare / Issue 2/2024
Print ISSN: 0176-1714
Electronic ISSN: 1432-217X
DOI: https://doi.org/10.1007/s00355-024-01535-0

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Probabilistic models of profiles for voting by evaluation

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Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

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