A networked voting rule for democratic representation
Financiación H2020 / H2020 Funds
Resumen: We introduce a general framework for exploring the problem of selecting a committee of representatives with the aim of studying a networked voting rule based on a decentralized large-scale platform, which can assure a strong accountability of the elected. The results of our simulations suggest that this algorithm-based approach is able to obtain a high representativeness for relatively small committees, performing even better than a classical voting rule based on a closed list of candidates. We show that a general relation between committee size and representatives exists in the form of an inverse square root law and that the normalized committee size approximately scales with the inverse of the community size, allowing the scalability to very large populations. These findings are not strongly influenced by the different networks used to describe the individuals’ interactions, except for the presence of few individuals with very high connectivity which can have a marginal negative effect in the committee selection process.
Idioma: Inglés
DOI: 10.1098/rsos.172265
Año: 2018
Publicado en: Royal Society Open Science 5, 3 (2018), 172265 [9 pp]
ISSN: 2054-5703

Factor impacto JCR: 2.515 (2018)
Categ. JCR: MULTIDISCIPLINARY SCIENCES rank: 25 / 69 = 0.362 (2018) - Q2 - T2
Factor impacto SCIMAGO: 1.131 - Multidisciplinary (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/FENOL-GROUP
Financiación: info:eu-repo/grantAgreement/EC/H2020/662725/EU/Bridging the gap: from Individual Behaviour to the Socio-tEchnical MaN/IBSEN
Financiación: info:eu-repo/grantAgreement/ES/MINECO/FIS2014-55867-P
Tipo y forma: Article (Published version)
Área (Departamento): Área Física Teórica (Dpto. Física Teórica)

Creative Commons You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.


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 Record created 2018-05-08, last modified 2020-01-17


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