Uncovering the social dynamics of online elections

Past work analysing elections in online domains has largely ignored the underlying social networks present in such environments. Here, the Wikipedia Request for Adminship (RfA) process is studied within the context of a social network and several factors influencing different stages of the voting pr...

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Detalles Bibliográficos
Autores: Lee, John Boaz, Cabunducan, Gerard, Cabarle, Francis George C., Castillo, Raphael, Maliano, Jasmine A.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2012
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/156306
Acceso en línea:https://hdl.handle.net/11441/156306
https://doi.org/doi: 10.3217/jucs-018-04-0487
Access Level:acceso abierto
Palabra clave:Election analysis
Logistic regression
Social influence
Social network analysis
Social voter
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spelling Uncovering the social dynamics of online electionsLee, John BoazCabunducan, GerardCabarle, Francis George C.Castillo, RaphaelMaliano, Jasmine A.Election analysisLogistic regressionSocial influenceSocial network analysisSocial voterPast work analysing elections in online domains has largely ignored the underlying social networks present in such environments. Here, the Wikipedia Request for Adminship (RfA) process is studied within the context of a social network and several factors influencing different stages of the voting process are pinpointed. Machine-learning problems were formulated to test the identified factors. The different facets explored are: election participation, decision making in elections, and election outcome. Our results show that voters tend to participate in elections that their contacts have participated in. Furthermore, there is evidence showing that an individual's decision-making is influenced by his contacts' actions. The properties of voters within the social graph were also studied; results reveal that candidates who gain the support of an influential coalition tend to succeed in elections. Additionally, detailed analyses on different classes of voters and candidates were made. Finally, the structural properties corresponding to networks of election participants were analysed and these networks were found to exhibit higher degrees of community structure versus graphs of participants selected at random.Lenguajes y Sistemas Informáticos2012info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/156306https://doi.org/doi: 10.3217/jucs-018-04-0487reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésJUCS - Journal of Universal Computer Science, 18 (4), 487-506.https://lib.jucs.org/article/23081/info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1563062026-06-17T12:51:07Z
dc.title.none.fl_str_mv Uncovering the social dynamics of online elections
title Uncovering the social dynamics of online elections
spellingShingle Uncovering the social dynamics of online elections
Lee, John Boaz
Election analysis
Logistic regression
Social influence
Social network analysis
Social voter
title_short Uncovering the social dynamics of online elections
title_full Uncovering the social dynamics of online elections
title_fullStr Uncovering the social dynamics of online elections
title_full_unstemmed Uncovering the social dynamics of online elections
title_sort Uncovering the social dynamics of online elections
dc.creator.none.fl_str_mv Lee, John Boaz
Cabunducan, Gerard
Cabarle, Francis George C.
Castillo, Raphael
Maliano, Jasmine A.
author Lee, John Boaz
author_facet Lee, John Boaz
Cabunducan, Gerard
Cabarle, Francis George C.
Castillo, Raphael
Maliano, Jasmine A.
author_role author
author2 Cabunducan, Gerard
Cabarle, Francis George C.
Castillo, Raphael
Maliano, Jasmine A.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Lenguajes y Sistemas Informáticos
dc.subject.none.fl_str_mv Election analysis
Logistic regression
Social influence
Social network analysis
Social voter
topic Election analysis
Logistic regression
Social influence
Social network analysis
Social voter
description Past work analysing elections in online domains has largely ignored the underlying social networks present in such environments. Here, the Wikipedia Request for Adminship (RfA) process is studied within the context of a social network and several factors influencing different stages of the voting process are pinpointed. Machine-learning problems were formulated to test the identified factors. The different facets explored are: election participation, decision making in elections, and election outcome. Our results show that voters tend to participate in elections that their contacts have participated in. Furthermore, there is evidence showing that an individual's decision-making is influenced by his contacts' actions. The properties of voters within the social graph were also studied; results reveal that candidates who gain the support of an influential coalition tend to succeed in elections. Additionally, detailed analyses on different classes of voters and candidates were made. Finally, the structural properties corresponding to networks of election participants were analysed and these networks were found to exhibit higher degrees of community structure versus graphs of participants selected at random.
publishDate 2012
dc.date.none.fl_str_mv 2012
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/156306
https://doi.org/doi: 10.3217/jucs-018-04-0487
url https://hdl.handle.net/11441/156306
https://doi.org/doi: 10.3217/jucs-018-04-0487
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv JUCS - Journal of Universal Computer Science, 18 (4), 487-506.
https://lib.jucs.org/article/23081/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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